PhysioNet News

Conference on Health, Inference, and Learning (CHIL): Submit your paper by Mon 5 Feb, 2024!

30 Jan 2024 10:27 -0500

The 2024 Conference on Health, Inference, and Learning (CHIL) invites submissions focused on artificial intelligence and machine learning (AI/ML) techniques that address challenges in health, which includes clinical healthcare, public health, health economics, informatics, and more. For full details, refer to the online Call for Papers: https://www.chilconference.org/call-for-papers.html

This year, CHIL 2024 will accept submissions for three distinct tracks: Models and Methods, Applications and Practice, and Policy, Impact and Society. Accepted papers will be published in the Proceedings of Machine Learning Research (PMLR). We are also offering Best Paper Awards to recognize outstanding work across all tracks.

Submissions are due on February 5th, 11:59 PM EST in the form of anonymized PDF files. All submissions for CHIL 2024 will be managed through the OpenReview system. Similar to last year, we have a full author response period and reviewer discussion period to ensure proper feedback on the work.

Hosted by The Association of Health, Learning, and Inference (AHLI), the CHIL conferences have consistently served as premier scientific meetings, uniting clinicians and researchers from both industry and academia, and weaving a rich tapestry of knowledge and innovation.

Building on a series of conferences and events since 2019, CHIL has persistently set a benchmark in interdisciplinary research within the realms of machine learning and health, demonstrated through its impactful sessions (2020, 2021, 2022, 2023). Following the resounding success of CHIL 2023 at the Broad Institute, Cambridge, we are thrilled to announce that CHIL 2024 will continue fostering insightful discussions and collaborations in the field. The 5th annual conference will take place in-person from June 27-28 at the Verizon Executive Education Center at Cornell Tech in New York City.

Important Dates

Submissions due: Feb 5, 2024 at 11:59pm
Bidding opens for reviewers: Feb 6, 2024 at 11:59pm
Reviews released: Mar 4, 2024 by 11:59pm
Author/Reviewer discussion period: Mar 10-21, 2024
Author notification: Apr 3, 2024 by 11:59pm
CHIL conference: June 27-28, 2024

George B. Moody PhysioNet Challenge 2024: Challenge Opening

26 Jan 2024 13:24 -0500

We are delighted to announce the opening of the George B. Moody PhysioNet Challenge 2024. The 2024 Challenge invites teams to develop algorithms for digitizing and classifying electrocardiograms (ECGs) captured from images or paper printouts.

Despite recent advances in digital ECG devices, paper or physical ECGs remain common, especially in the Global South. These paper ECGs document the history and diversity of cardiovascular diseases (CVDs), and algorithms that can digitize and classify these images have the potential to improve our understanding and treatment of CVDs, especially for underrepresented and underserved populations.

We have shared example code and scoring code in both MATLAB and Python and synthetic ECG generation code in Python. While last year’s Challenge had the largest dataset yet, this year’s Challenge begins with a much more tractable dataset that you may already have on your machine, and you can use the provided code to create ECG images with realistic artifacts. We will also augment these data to create a much richer and more representative dataset, so stay tuned for more announcements. We will open the scoring system in the coming days.

See the Challenge website for more information, rules and deadlines: https://physionetchallenges.org/2024/

As in previous years, we have divided the Challenge into two phases: an unofficial phase and an official phase. The unofficial phase solicits feedback from the research community (i.e., you) to help us to improve the Challenge for the official phase, so we require teams to register and participate in the unofficial phase of the Challenge to be eligible for a prize. Please enter early and often – we need you to look for quirks in our data, our scoring system, and otherwise. We are imperfect (and bandwidth-limited), so please send us suggestions via the forum (see below). We rely on the community to help us to improve the quality of the Challenge each year.

More information will be posted on the PhysioNet Challenge website and the Challenge forum as it becomes available. Please post questions and comments to the Challenge forum as well. However, if your question reveals information about your entry, then please email info [at] physionetchallenge.org instead to help us safeguard the diversity of approaches to the Challenge. We may post parts of our replies publicly if we feel that all Challengers should benefit from the information contained in our responses. We will not answer emails about the Challenge sent to other email addresses.

Many thanks again for your continued support of this event, and we hope that you enjoy the 2024 Challenge!

Call for Papers on Computational Tools for Physiological Time Series Analysis

22 Jan 2024 15:48 -0500

On behalf of our colleagues, we are pleased to announce a call for papers for a focus collection in IOP Physiological Measurement on the topic of "Open Source and Validated Computational Tools for Physiological Time Series Analysis".

Physiological time series analysis plays a crucial role in understanding the complex dynamics of biological systems and their response to stimuli and interventions. The availability of reliable, open-source computational tools is essential for advancing research in this field, facilitating reproducibility, promoting collaboration, and accelerating scientific discoveries.

This focus collection aims to showcase the latest advancements in open-source tools and methodologies that have been rigorously validated for the analysis of physiological time series data.

Guest Editors

Joachim A. Behar, Technion Institute of Technology, Israel
Peter H. Charlton, University of Cambridge, UK
Márton Áron Goda, Technion Institute of Technology, Israel
Maarten De Vos, KU Leuven, Belgium

For questions, please contact Dr. Joachim A. Behar (jbehar@technion.ac.il).

Announcing the SNOMED CT Entity Linking Challenge

20 Dec 2023 11:53 -0500

We are pleased to announce the launch of the SNOMED CT Entity Linking Challenge in collaboration with SNOMED International, Veratai, and DrivenData. Sponsored by SNOMED International, the challenge seeks to advance the development of Entity Linking models that operate on unstructured clinical text.

Participants are tasked with developing a model to annotate MIMIC-IV-Note discharge summaries with SNOMED CT concepts. Training data, comprising ~300 annotated discharge summaries, has been made available on PhysioNet at https://doi.org/10.13026/s48e-sp45.

PhD opportunities at the European INSIDE-HEART consortium (deadline for applications: 31 Jan 2024)

11 Dec 2023 13:50 -0500

INSIDE-HEART brings together universities, companies and hospitals from Italy, Finland, France, Israel, Netherlands, Spain, and Sweden to establish a multi-disciplinary network to tackle the design and early-phase validation of digital biomarkers targeting the diagnosis of supraventricular arrhythmias (SVAs) and their associated potential for adverse risk assessment.

Our colleagues in the network are looking for 10 motivated PhD candidates, funded by the European Union’s Horizon Europe program under the Marie Skłodowska Curie Actions. For further information and details on how to apply, see: https://www.inside-heart.eu/recruitment/. The call for applications is open until 31 January 2024.

The INSIDE-HEART project is coordinated by the Politecnico di Milano. Please direct questions to insideheart@polimi.it

DARPA Triage Challenge: Qualification extended through Nov 27

6 Nov 2023 16:07 -0500

Qualification for the DARPA Triage Challenge has been extended through November 27, 2023 at 23:59. We encourage you to join the challenge as a self-funded team for the Systems, Virtual and Data Competitions. You may compete in one or more challenge tracks, where qualification must be entered for each track individually.

To register, please visit the Team Qualification Portal at: https://events.sa-meetings.com/DTCTeamPortal/.

For more information on the challenge, see: https://triagechallenge.darpa.mil/ or contact TriageChallenge@darpa.mil.

Join the DARPA Triage Challenge! Deadline for registration: Monday 13 November, 2023

18 Oct 2023 11:10 -0400

The Defense Advanced Research Projects Agency (DARPA), a research and development agency within the Department of Defense, is seeking competitors for a new medical response challenge. The DARPA Triage Challenge aims to drive breakthrough innovations that improve medical response time during mass casualty incidents in complex military and civilian settings, especially when medical resources are limited relative to the need.

The challenge includes a series of technical challenge events to drive breakthrough innovations in the identification of physiological features (signatures) of injury, and help medical responders perform scalable, timely, and accurate triage. The challenge has two primary triage competitions – Systems and Virtual – and a secondary triage Data competition. The Systems and Virtual competitions focus on stand-off sensing of physiological data using autonomous platforms – uncrewed aerial and ground vehicles – during primary triage. Competitors will conduct real-time sensor data analysis to identify casualties for urgent hands-on evaluation by medical personnel.

Relevant to the PhysioNet community, the Data competition seeks to identify physiological signatures of injury derived from data captured by non-invasive sensors (contact-based or stand-off). Such advances could accelerate responders’ anticipatory decisions and prioritization for medical care during secondary triage. Competitors will attempt to develop algorithms that detect signatures in these data streams to provide decision support appropriate for austere and complex pre-hospital settings. Of particular interest are early signatures indicating a need for life-saving interventions against conditions that medics are trained and equipped to treat during secondary triage, such as hemorrhage and airway injuries.

The Data competition will use DARPA-provided de-identified, multi-modal physiological data from trauma patients across diverse settings and cohorts provided by the DARPA Research Infrastructure for Trauma with Medical Observations effort. Data types include, but are not limited, to: photoplethysmography (PPG) waveforms, medical procedures, imaging results and video footage during prehospital helicopter transport and in the trauma bay.

Prizes for year one:

Systems Competition: Up to $200K Prize pool
Virtual Competition: Up to $100K Prize pool
Data Competition: Up to $200K Prize pool

Total Prizes $7M over three challenges

DARPA is currently seeking self-funded competitors. Join us by registering on the Qualification Portal, now through Nov. 13, 2023.

For more information visit the DARPA Triage Challenge website.

Call for partners interested in synthetic patient data

27 Sep 2023 15:44 -0400

The Google Research team is looking for partners to understand the needs and requirements for synthetic data. They have capabilities to generate both structured and unstructured patient data as well as images for infrastructure testing and medical research. Please contact us if you are interested in the partnership.

MIMIC-IV-ECG module released

15 Sep 2023 16:14 -0400

The MIMIC-IV-ECG module is now available. This module contains approximately 800,000 diagnostic electrocardiograms across nearly 160,000 unique patients. The vast majority of ECGs for patients who appear in the MIMIC-IV Clinical Database are included. The patients in MIMIC-IV-ECG have been matched against the MIMIC-IV Clinical Database, making it possible to link to information across the MIMIC-IV modules. When a cardiologist report is available for a given ECG, we provide information for linking to it.

FFA-IR dataset is unavailable until further notice

6 Sep 2023 15:48 -0400

The authors of the FFA-IR dataset have asked for downloads to be disabled until further notice to adhere with local policy changes. We apologize for the inconvenience and hope to make the files available again in the future.

I-CARE is now available on Google Cloud

22 Jun 2023 13:23 -0400

I-CARE v.2.0 is now available on Google Cloud. For details on downloading the dataset or working with it directly in the cloud, see the Files section of the project description.

Announcing CXR-LT, a competition for long-tailed disease classification on chest X-rays

21 Jun 2023 09:47 -0400

We are pleased to announce CXR-LT, a competition on Multi-Label Long-Tailed Classification on Chest X-Rays. Many real-world problems, including diagnostic medical imaging exams, are “long-tailed”: there are a few common findings followed by more relatively rare conditions. This competition will provide a challenging large-scale multi-label long-tailed learning task on chest X-rays (CXRs), encouraging community engagement with this emerging interdisciplinary topic.

CXR-LT is organized as a shared task for the workshop on Computer Vision for Automated Medical Diagnosis (CVAMD) held in association with the International Conference on Computer Vision (ICCV) 2023. Participants will be invited to submit their solutions for publication presentation at CVAMD 2023 and publication in the ICCV 2023 workshop proceedings.

The challenge uses an expanded version of MIMIC-CXR-JPG v2.0.0, a large benchmark dataset for automated thorax disease classification. Each CXR study in the dataset was labeled with 12 newly added disease findings extracted from the associated radiology reports. The resulting long-tailed (LT) dataset contains 377,110 CXRs, each labeled with at least one of 26 clinical findings (including a "No Finding" class).

Important dates

05/01/2023: Development Phase begins. Participants can begin making submissions and tracking results on the public leaderboard.
07/14/2023: Testing Phase begins. Unlabeled test data will be released to registered participants. The leaderboard will be kept private for this phase.
07/17/2023: Competition ends. Participants are invited to submit their solutions as 8-page papers to ICCV CVAMD 2023!
07/28/2023: ICCV CVAMD 2023 submission deadline. (Competition participants may receive an extension if needed.)
08/11/2023: ICCV CVAMD 2023 acceptance notification.
10/06/2023: ICCV CVAMD 2023 workshop.

This competition is supported in part by the Artificial Intelligence Journal (AIJ). For any questions, please contact cxr.lt.competition.2023@gmail.com.

I-CARE will shortly be available on Google Cloud

20 Jun 2023 12:07 -0400

We are aware that downloading the I-CARE dataset from PhysioNet is currently slow and we apologize for the inconvenience. To resolve this issue, we are currently transferring the dataset to Google Cloud. Once the transfer is complete, the dataset can be analyzed directly in the cloud or downloaded using Google Cloud Utilities. Please check here for updates.

Google Health collaborate with PhysioNet to release open-source medical foundation models

25 Apr 2023 22:56 -0400

We are excited to announce the release of Medical AI Research Foundations — a repository of open-source medical foundation models and a collaboration between Google Health and PhysioNet. Our goal in releasing this collection of resources is to accelerate medical AI research and to democratize access to foundational medical AI models.

We are seeding Medical AI Research Foundations with REMEDIS models for chest X-ray and pathology (with related Github code). We expect to add more models and resources for training medical foundation models such as datasets and benchmarks in the future. We also welcome contributions from the medical AI research community.

Responsible use of MIMIC data with online services like GPT

18 Apr 2023 15:07 -0400

We have received inquiries regarding the use of credentialed data (MIMIC-III, MIMIC-IV, MIMIC-CXR) with online services such as GPT. The PhysioNet Credentialed Data Use Agreement explicitly prohibits sharing access to the data with third parties, including sending it through APIs provided by companies like OpenAI, or using it in online platforms like ChatGPT.

If you are interested in using the GPT family of models, we recommend enrolling in the Azure OpenAI service. You'll need to opt out of human review of the data, as (1) you are processing sensitive data where the likelihood of harmful outputs and/or misuse is low, and (2) you do not have the right to permit Microsoft to process the data for abuse detection due to the data use agreement you have signed. The form for opting out of the review process is available here: https://aka.ms/oai/additionalusecase

If you have any questions about this policy, feel free to reach out: https://physionet.org/about/#contact_us

Opportunity to join the KCL EnPRO Lab on a music-physiology data science PhD scholarship

17 Apr 2023 09:27 -0400

The EnPRO Lab in the Department of Engineering and School of Biomedical Engineering & Imaging Sciences at King's College London is looking to fill a music-physiology data science doctoral scholarship which is now open to international applicants for October 2023 entry. The successful applicant will join the research team of the ERC COSMOS project (cosmos.isd.kcl.ac.uk).

The research investigates the impact of music expressivity on the autonomic nervous system. The project focuses on developing individualized, explanatory computational models for modulating autonomic responses through music that can be used in digital therapeutics for cardiovascular health. The scientific approach will be based on studying the interactions between musical prosody (acoustic variations introduced in musical communication) and autonomic parameters such as heart rate, heart rate variability, respiration, and blood pressure. The methods build on software tools developed in the COSMOS project.

The research activities will include study design, ethics application, data collection, data processing, computational modelling, and analysis and interpretation of results, and disseminating results through publications and conference presentations. The ideal candidate will be knowledgeable in Python, Matlab, or R, and have a Bachelors or Masters degree in biomedical engineering, mathematical and computational sciences, music information research, or a related discipline. Experience in analysis of biosignals and/or music signals, or industrial experience is desirable.

Funding is available for 3.5 years, covers fees and stipend, and standard computing/travel support. For further details, please see the job posting.

Competition announced: Detecting Parkinson's freezing of gait using wearable sensor data

28 Mar 2023 21:44 -0400

An estimated 7 to 10 million people around the world have Parkinson’s disease, many of whom suffer from freezing of gait (FOG). FOG are unpredictable, unexpected, involuntary episodic events. During a FOG episode, patients report that their feet are inexplicably “glued” to the ground, preventing them from moving forward despite their attempts.

PhysioNet contributor Jeff Hausdorff and his colleagues at the Tel Aviv Sourasky Medical Center, KU Leuven, and Harvard Medical School, have contributed a large dataset to a machine learning contest that was recently launched to automatically detect FOG episodes and to address the shortcomings of existing methods.

This work has the potential to help advance the evaluation, understanding, and treatment of FOG, and, ultimately, to improve the lives of the many people who suffer from this debilitating Parkinson’s disease symptom. To join the competition, visit Kaggle.

Timeline

June 1, 2023: Entry Deadline. You must accept the competition rules before this date in order to compete.
June 1, 2023: Team Merger Deadline. This is the last day participants may join or merge teams.
June 8, 2023: Final Submission Deadline.

Prizes

1st Place: $40,000
2nd Place: $25,000
3rd Place: $20,000
4th Place: $10,000
5th Place: $5,000

Toronto Health Datathon (23-24 February 2023)

10 Mar 2023 11:22 -0500

Over 45 students, academics, clinicians, and engineers gathered at the Google Canada offices on 23-24 February for the Toronto Health Datathon 2023. Participants used anonymized real-world data from Health Data Nexus to develop machine learning models aimed at solving real-world problems facing Canadian healthcare.

Over the past two years, PhysioNet has been collaborating with Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM) at the University of Toronto to develop the software that underpins both Health Data Nexus and PhysioNet. We look forward to continuing this collaboration, working towards tight integration between the two platforms.

Tokyo Datathon on Machine Learning in Healthcare (1-3 Sept 2023)

9 Mar 2023 11:13 -0500

We are excited to be supporting the 3rd Tokyo Datathon on Machine Learning in Healthcare, co-organized by Tokyo Medical and Dental University and MIT Critical Data. The event will be held on 1-3 September 2023 and will bring together experts from across healthcare and data science to tackle clinical questions.

Registration and event details will be posted on the Datathon Website. If you are a Japanese-language speaker with experience with the MIMIC dataset and would be interested in helping as a mentor at the event, please reach out to Leo Anthony Celi.

PhysioNet 2023 Challenge Opening

22 Feb 2023 11:34 -0500

We are delighted to announce the opening of the George B. Moody PhysioNet Challenge 2023. This year’s Challenge invites teams to use electroencephalogram (EEG) recordings to predict the neurological recovery of patients from coma in the hours following resuscitation from cardiac arrest. This Challenge leverages a novel database of over 1,000 subjects from seven hospitals who together underwent over 50,000 hours of EEG monitoring. As always, the team with the best score for this task on the hidden test set wins the Challenge.

We have shared data, example code, and scoring code in both MATLAB and Python, and we will open the scoring system in the coming weeks. As in previous years, we have divided the Challenge into two phases: an unofficial phase and an official phase. The unofficial phase solicits feedback from the research community (i.e., you) to help us to improve the Challenge for the official phase, so we require teams to register and participate in the unofficial phase of the Challenge to be eligible for a prize. Please enter early and often – we need you to look for and share the quirks in our data, our scoring system, and otherwise.

Please see the Challenge website and the Challenge forum for more information, rules and deadlines: https://physionetchallenges.org/2023/
https://groups.google.com/g/physionet-challenges/

Many thanks again for your continued support of this event, and we hope that you enjoy the 2023 Challenge.

Dataworks! Prizes Awarded to PhysioNet Challenge and MIT Critical Data teams

22 Feb 2023 11:32 -0500

We are delighted to announce that the George B. Moody PhysioNet Challenges were awarded the "Distinguished Achievement Award for Data Reuse, as part of the DataWorks! Prize, while MIT Critical Data was awarded "Significant Achievement Award for Data Sharing".

Launched on May 11, 2022, the Data Works! Prize was created in partnership between the NIH Office of Data Science Strategy and the Federation of American Societies for Experimental Biology (FASEB) to highlight the critical role of data sharing and reuse in scientific discovery.

George B. Moody designed and led the Challenges from 2000 to 2015. Prof. Clifford has led the Challenges since 2015 and has been a key contributor to its parent resource, PhysioNet (The Research Resource for Complex Physiologic Signals), for over two decades. Prof. Reyna has co-led the PhysioNet Challenges since 2019, and has been instrumental in the development of its repeatable science standards.

MIT Critical Data, led by the Laboratory for Computational Physiology, builds communities around the world across disciplines to derive knowledge from data routinely collected in the process of care in order to understand health and disease better, and in the local context. Its flagship project is the Medical Information Mart for Intensive Care, or the MIMIC database.

More on the DataWorks! Prize here: https://datascience.nih.gov/director/directors-blog-dataworks-winners-2023 and the PhysioNet Challenges here: https://physionetchallenges.org/faq and MIT Critical Data here: https://criticaldata.mit.edu/.

PhysioNet and MIMIC are supported by the National Institute of Biomedical Imaging and Bioengineering.

Opportunity to join the UCSF Hypoxia Lab as Data Analyst

8 Feb 2023 14:30 -0500

Our colleagues at UCSF Department of Anesthesia, The UCSF Hypoxia Lab (hypoxialab.org) and the UCSF Center for Health Equity in Surgery and Anesthesia (chesa.ucsf.edu) are seeking a full-time Data Analyst (with data engineering skills) to join their Open Oximetry project.

This project seeks to understand the potential impact of skin color on accuracy of pulse oximetry and other medical diagnostic devices. The Data Analyst will work at the intersection of health diagnostics, health equity and AI in the world’s leading lab (hypoxialab.org) for this type of research along with a team of experts who have published some of the seminal research on this topic.

As part of the project, the team will be setting up robust data collection systems in the lab and the hospital settings as well as creating and managing an open access data repository for diagnostics device data. This repository will contain data from our lab as well as data from collaborating study groups. The data will be shared via portals that facilitate raw data utilization for researchers and industry, as well as visualized data to help lay persons and consumers better understand device technology performance and standards.

The Data Analyst will work closely with the laboratory-based clinical research team to gather, analyze, and interpret a wide variety of research data; Design and conduct research including selecting data, developing research instruments, analyzing collected information according to established statistical methods, and developing recommendations based on research findings; Prepare reports, charts, tables, and other visual aids to interpret and communicate data and results; Create and manage data repositories; work with our AI/ML team to test novel analytic methods with our data. The ideal candidate will be knowledgeable in SQL and Python or R and have a Bachelors or Masters degree in Statistics, Data Science, or adjacent technical field.

This position is for a period of 12 months, though may be longer contingent on further funding. For further details, see the job posting.

BioNLP Workshop 2023: Problem List Summarization

19 Jan 2023 13:03 -0500

We are excited to announce the launch of a shared task on problem list summarization at the BioNLP Workshop 2023. The goal for participants is to generate a list of diagnoses and problems in a patient’s daily care plan using input from the provider’s progress notes during hospitalization. The task contains 768 progress notes for training, and 300 progress notes for evaluation. The goal of this shared task is to attract future research efforts in building NLP models for real-world decision support applications, where a system generating relevant and accurate diagnoses will assist the healthcare providers’ decision-making process and improve the quality of care for patients.

Participants will be tasked with developing NLP systems for EHR summarization. Participants who design novel systems and achieve competitive performance in the shared task, running from January to April 2023, will be invited to present their results at the BioNLP Workshop, which will be held in Toronto, Canada and co-located with ACL 2023. The challenge is open to anyone interested in clinical NLP and medical AI. We encourage individuals, teams, and organizations to participate.

To register for the challenge, please visit: https://forms.gle/geTXN6Z1pyfC55Fn8. More information about the challenge, including the official rules and guidelines, can be found at: https://physionet.org/content/bionlp-workshop-2023-task-1a/. You are welcome to join our google discussion group for newest update: https://groups.google.com/g/bionlp2023problemsumm

SOAP Note Tagging and Problem List Summarization dataset: Files unavailable until July 13th, 2023

19 Jan 2023 12:59 -0500

The SOAP Note Tagging and Problem List Summarization dataset dataset is temporarily unavailable as it is part of an ongoing shared task of BioNLP Workshop 2023: 1A (Problem List Summarization). The dataset will be made available on July 13th, 2023. More details about the workshop and shared task can be found at: https://doi.org/10.13026/s8wk-ja78

We apologize for any inconvenience this may cause and appreciate your understanding. We will provide updates as soon as more information becomes available. A new test set with 300 progress notes will be released along with the original set of 768 notes when the embargo is lifted. If you are interested in signing up the shared task, register here: https://forms.gle/geTXN6Z1pyfC55Fn8

MIMIC-IV-ECG module released to consortium members

23 Dec 2022 15:02 -0500

A beta release of the MIMIC-IV-ECG module is now available to MIT Critical Data Consortium members. The MIMIC-IV-ECG module contains approximately 800,000 diagnostic electrocardiograms across nearly 160,000 unique patients. All of the ECGs for patients who appear in the MIMIC-IV Clinical Database are included. When a cardiologist report is available for a given ECG, it is also provided. The patients in MIMIC-IV-ECG have been matched against the MIMIC-IV Clinical Database, making it possible to link to information across the MIMIC-IV modules.

A public version of this dataset will be released in approximately six months. During the embargo period we will be carrying out additional tests and data quality checks.

Support Our Colleagues in the NIH DataWorks Challenge!

6 Dec 2022 13:18 -0500

Congratulations to our colleagues who have been selected as finalists for the National Institutes of Health DataWorks Challenge!

Please support one of these teams working to share and reuse data in research and scientific discovery (The link will take you directly to the page to submit a vote). Voting is open until December 21, 2022. Unfortunately, you may only vote for one team, but they can both be awarded prizes. Please share and promote awareness to increase our colleagues’ chances!

MIT Critical Data
https://www.herox.com/dataworks/round/2457/entry/41104

MIT Critical Data builds communities across disciplines to derive knowledge from health records to understand health and disease better. Help them continue to build valuable research resources such as MIMIC and freely accessible educational resources.

PhysioNet Challenges
https://www.herox.com/dataworks/round/2457/entry/41376

The PhysioNet Challenges are annual data science competitions that ask what we can learn from data to improve health and healthcare. Help the team draw out unrealized value from data and advance data reuse and algorithm development.

Background

The Federation of American Societies for Experimental Biology (FASEB) and the National Institutes of Health (NIH) are championing a bold vision of data sharing and reuse. The DataWorks! Prize fuels this vision with an annual challenge that showcases the benefits of research data management while recognizing and rewarding teams whose research demonstrates the power of data sharing or reuse practices to advance scientific discovery and human health. The future of biological and biomedical research hinges on researchers’ ability to share and reuse data. Sharing and reuse had a sizable, catalytic impact on the development of COVID-19 vaccines and treatment protocols. The DataWorks! Prize is an opportunity for the research community to share their stories about the practices, big and small, that lead to scientific discovery.

PhysioNet receives inaugural MIT Prize for Open Data

10 Nov 2022 12:11 -0500

The PhysioNet team were recipients of the inaugural MIT Prize for Open Data in recognition of their work to support health research and education. The award - established to highlight the value of open data at MIT - was presented by School of Science Dean Nergis Mavalvala and MIT Libraries Director Chris Bourg on October 28 in the MIT Hayden Library.

Multimodal Physiological Monitoring During Virtual Reality Piloting Tasks: CogPilot Data Challenge

8 Sep 2022 09:54 -0400

We are pleased to announce the publication of a dataset comprising multimodal physiologic, flight performance, and user interaction data streams, collected as participants performed virtual-reality flight tasks of varying difficulty.

With over an hour of highly multimodal physiological and behavioral signals collected on each of the thirty-five participants, the dataset represents a unique opportunity to develop analytics and models linking an individual’s physiology to their behavior and performance in tasks of varying difficulty.

More data are being collected and will be uploaded to PhysioNet periodically. The data underpins the CogPilot Data Challenge, which explores how performance measurements and physiological data can be used to assess the competency of student pilots. To participate in the CogPilot Challenge, visit: https://pilotperformance.mit.edu/

Announcing the MIMIC-IV Waveforms

9 Aug 2022 09:44 -0400

We are pleased to announce an initial release of a version (0.1.0) of the MIMIC-IV-Waveform module. These waveforms are a rich source of patient information - including ECG, PPG, and Blood Pressure signals - and can be linked to the clinical information in MIMIC-IV. This initial release contains 200 records from 198 patients. An upcoming release will include around 10,000 records.

The dataset was the subject of a workshop at IEEE EMBC in July of 2022, led by Peter Charlton, which demonstrated how to use the WFDB-Python package to extract and analyze waveform features. Executable notebooks and tutorial materials are available at: https://mimic.mit.edu/docs/iv/tutorials/waveform/ieee_workshop/ .

Rethinking Algorithm Performance Metrics for Artificial Intelligence in Diagnostic Medicine

29 Jul 2022 16:09 -0400

Gari Clifford and Matthew Reyna from Emory University and Elaine Nsoesie from Boston University recently published an invited viewpoint in The Journal of the American Medical Association on "Rethinking Algorithm Performance Metrics for Artificial Intelligence in Diagnostic Medicine". The viewpoint focuses on how we often use the wrong optimization targets when applying machine learning to medical data, and how we can address this issue, and is part of the Gordon and Betty Moore Foundation's broader series on Diagnostic Excellence.

Server maintenance between 15-18 July 2022 (https://archive.physionet.org/ will be unavailable)

17 Jul 2022 20:15 -0400

Our servers at MIT are undergoing and testing and maintenance work between Friday 15th and Monday 18th July 2022. PhysioNet (https://physionet.org/) will remain active during this period, but some services may be affected (for example, the archive website https://archive.physionet.org/).

Trust Markers with ORCID

30 Jun 2022 13:42 -0400

Linking an ORCID to your PhysioNet profile can help us to quickly verify your identity, speeding up the process of gaining access to datasets such as MIMIC.

When reviewing an ORCID profile, we look out for “Trust Markers” which are pieces of information added to the profile by groups such publishers and employers.

To find out more about how PhysioNet is working with ORCID, see their blog post on how we are using the Trust Markers to streamline the data credentialing process.

Significant delays are expected to applications for credentialed access to PhysioNet.

7 Apr 2022 09:47 -0400

We are currently dealing with a high volume of applications for credentialed access to PhysioNet, so please expect significant delays (up to 45 days) in the review process. We are doing our best to deal with the waitlist quickly, handling applications in the order in which they are received. To help ensure that your application is successful, please remember to:

Include a copy of your CITI training report (not the certificate).
Remind your reference to reply promptly when contacted.
Check your application details are correct before submitting.
Add an institutional or educational email address as your primary email.

We apologize for the inconvenience. Please bear with us during this busy time!

Interruption to the PhysioNet mail server between the 30th and 31st March 2022

31 Mar 2022 18:09 -0400

Between Wednesday 30 March and Thursday 31 March the PhysioNet mail server suffered an interruption. As a result, if you attempted to register for a new account or reset a password, you may not have received an email.

We are now in the process of resending emails, so please check your mailbox if an expected email did not arrive. We apologize for the inconvenience and we will be taking steps to prevent similar issues issue in the future.

Applying for access to protected datasets such as MIMIC is now a three step process

18 Mar 2022 20:41 -0400

Applying for access to protected datasets such as MIMIC is now a three step process:

Submit your personal details via the "Credentialing" page of your user profile.
Submit your training report via the "Training" page of your user profile.
Once the steps above are complete, sign the Data Use Agreement in the "Files" section of the relevant project. You can view your signed agreements on the "Agreements" page of your user profile.

The change helps us to review data access requests more efficiently and gives us the flexibility to support additional training courses in future.

Forthcoming changes to the credentialing process

28 Feb 2022 10:38 -0500

When applying for access to datasets such as MIMIC, you are currently required to submit a single "credentialing" application that allows us to check both CITI training status and identity.

We will soon be releasing updates to PhysioNet that will require training and identity details to be submitted independently. As a result, a new "Training" tab will be added to your user profile.

This change will allow us to support different types of training for different datasets (for example, an Australian dataset may require training on specific issues relating to Australia). The change will also help us to streamline the review process.

PhysioNet Challenge 2022 Announcement

31 Jan 2022 18:31 -0500

Dear Community,

We have two big announcements today. First, at last year’s Computing in Cardiology (CinC) Conference, the Board voted to rename the PhysioNet/Computing in Cardiology Challenges in honor of George Moody, and his life-long contributions to the field, and specifically PhysioNet, the Challenges and CinC. The Challenge is now called the “The George B. Moody PhysioNet Challenge”. For consistency, we will still abbreviate this to the PhysioNet Challenge. We continue to partner with CinC, and will be awarding prizes in Finland in September this year.

Second, we are delighted to also announce the opening of the George B. Moody PhysioNet Challenge 2022. This year’s Challenge aims to identify the presence, absence, or unclear cases of murmur waves in heart sound recordings collected from multiple auscultation locations on the body using a digital stethoscope. Building on our successful Challenge from 2016, together with our generous collaborators at the Universidade Portucalense and Universidade do Porto, we have sourced a database of 5272 recordings from 1568 inhabitants of Pernambuco state, Brazil during two independent cardiac screening campaigns which were designed to support the development of a telemedicine network. More details on the data can be found in a recent publication in the IEEE Journal of Biomedical and Health Informatics.

Demo code in Python and MATLAB is available, and the scoring system will be open later in February - Look out for the announcement very soon!

See here for more information, rules and deadlines: https://moody-challenge.physionet.org/2022/

As with previous years, we have divided the Challenge into two phases. The first (unofficial phase) is to enable the research community (i.e. you) to help us improve the Challenge. We value your input, and it is therefore compulsory to enter the Challenge in this unofficial phase (before 9th April) to be eligible for a prize. This is very important - we need your help! Please enter early and often - the score doesn’t matter and will be wiped from the board for the official phase. We need you to look for quirks in our scoring system, data formats, or anomalies in the raw data that do not make sense to you. We are not perfect, and are bandwidth-limited, and so we rely on the peer-review of our community to improve the quality of the Challenge every year. In particular, this year we strongly encourage suggestions for modifying our scoring function, which we are sure will be controversial.

Please note that you *must* re-register for this Challenge (using the link below) even if you competed last year and have no team changes, and to be eligible for a prize, you must submit at least one successful entry during the unofficial phase.

Quick links for this year's Challenge:

More information will be posted on the PhysioNet Challenge website as it is available. Please check the Challenge forum for real-time updates. Please also post questions and comments in the forum. However, if your question reveals information about your entry, then please email Info [at] physionetchallenge.org. We may post parts of our reply publicly if we feel that all Challengers should benefit from the information contained in our responses. We will not answer emails about the Challenge sent to other email addresses.

Many thanks again for your continued support of this event, and we hope that you enjoy the 2022 Challenge

-Gari, Matt, Ali and the PhysioNet Challenge Team

2020 and 2021 Challenges are complete

26 Jan 2022 00:00 -0500

Both the 2020 Challenge and the 2021 Challenge, which extended the 2020 Challenge, are now complete. The CinC articles for both Challenges are available on the CinC website here and here. The final scores can be found here. Please cite Perez Alday EA, Gu A, J Shah A, Robichaux C, Ian Wong AK, Liu C, Liu F, Bahrami Rad A, Elola A, Seyedi S, Li Q, Sharma A, Clifford GD^* Reyna MA^*. Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020. Physiol. Meas. 2021 Jan 1;41(12):124003. doi: 10.1088/1361-6579/abc960 to refer to the 2020 Challenge. Please also cite the standard PhysioNet citation. You can find followup articles to the 2020 Challenge in the 2021 Challenge and in the Journal of Physiological Measurement Focus Issue on Classification of Multilead ECGs.

2020 and 2021 Challenges are complete

26 Jan 2022 00:00 -0500

January 26, 2022: Both the 2020 Challenge and the 2021 Challenge, which extended the 2020 Challenge, are now complete. The CinC articles for both Challenges are available on the CinC website here and here. The final scores can be found here. Please cite Perez Alday EA, Gu A, J Shah A, Robichaux C, Ian Wong AK, Liu C, Liu F, Bahrami Rad A, Elola A, Seyedi S, Li Q, Sharma A, Clifford GD^* Reyna MA^*. Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020. Physiol. Meas. 2021 Jan 1;41(12):124003. doi: 10.1088/1361-6579/abc960 to refer to the 2020 Challenge. Please also cite Reyna MA, Sadr N, Perez Alday EA, Gu A, Shah AJ, Robichaux C, Rad AB, Elola A, Seyedi S, Ansari S, Ghanbari H, Li Q, Sharma A, Clifford GD. Will Two Do? Varying Dimensions in Electrocardiography: The PhysioNet/Computing in Cardiology Challenge 2021. Computing in Cardiology 2021; 48: 1-4 and Reyna MA, Sadr N, Perez Alday EA, Gu Annie, Shah AJ, Robichaux C, Rad AB, Elola A, Seyedi S, Ansari S, Ghanbari H, Li Q, Sharma A, Clifford GD. Issues in the automated classification of multilead ECGs using heterogeneous labels and populations. Preprint. 2022 to refer to the 2021 Challenge. Finally, please also cite the standard PhysioNet citation. You can find followup articles to the 2020 Challenge and the 2021 Challenge in the Journal of Physiological Measurement Focus Issue on Classification of Multilead ECGs.

Announcing BRAX, a Brazilian chest x-ray dataset labelled with 14 radiological findings

5 Jan 2022 17:08 -0500

We are pleased to announce publication of BRAX, a Brazilian chest x-ray dataset labelled with 14 radiological findings derived from Portuguese medical reports using NLP. BRAX contains 24,959 chest radiography exams and 40,967 images acquired in a large general Brazilian hospital.

Dr Eduardo Pontes Reis, co-author and Radiologist at Hospital Israelita Albert Einstein, notes the importance of datasets from underrepresented regions for evaluating how well clinical applications of deep learning can generalize to new populations and for reducing the lack of geographic diversity in publicly available chest x-ray data.

KURIAS-ECG is unavailable until further notice

30 Nov 2021 14:47 -0500

As a result of an internal audit at the Korea University Medical Center, the authors of the KURIAS-ECG dataset (https://doi.org/10.13026/kga0-0270) have asked for downloads to be disabled until further notice. We apologize for the inconvenience and hope to make the files available again in the future.

The PhysioNet/Computing in Cardiology Challenge entries are being evaluated

25 Oct 2021 01:00 -0400

October 25, 2021: We are currently evaluating entries on the 2021 Challenge test data in support of the Physiological Measurement focus issue on multilead ECG classification. The deadline to submit your code and a preprint is 1 December 2021, and the deadline to submit your article is 11 January 2022. See this forum announcement for details.

Winners of the PhysioNet/Computing in Cardiology Challenge 2021 announced

20 Sep 2021 01:00 -0400

September 20, 2021: The winners of the 2021 Challenge were announced on 15 September 2021 at CinC in Brno, Czech Republic. Congratulations, teams! See this page for the results and the full announcement for the final steps in this year’s Challenge, including details about the focus issue (deadline: 11 January 2022).

The challenges have been renamed to the George B. Moody PhysioNet Challenge in honor of George Moody

15 Sep 2021 01:00 -0400

September 15, 2021: In honor of the contributions of George Moody to PhysioNet and Computing in Cardiology, the Board of CinC voted to rename the Challenges to the George B. Moody PhysioNet Challenge.

Preparing CinC papers for the PhysioNet/Computing in Cardiology Challenge 2021

21 Jul 2021 01:00 -0400

July 21, 2021: As you prepare your CinC papers, please follow the CinC preparation and submission instructions and use either our LaTeX (Overleaf or download) or Word templates, which include important instructions, advice, and references. Please see here for more information, including our draft paper and important citation information.

MIMIC-IV demo available in the OMOP Common Data Model

28 Jun 2021 12:36 -0400

We are pleased to announce that a 100-patient demo of MIMIC-IV has been made available in the OMOP Common Data Model. The dataset is currently undergoing user testing and has known limitations (for example, the inputevents and outputevents tables are not yet incorporated). For more detail, please visit the project page on PhysioNet and the associated GitHub repository.

This work builds on previous efforts by Nicolas Paris, Adrien Parrot and colleagues on MIMIC-III. The project was in part supported by grants from Bill and Melinda Gates foundation and National Library of Medicine (NLM), National Institutes of Health.

PhysioNet is experiencing temporary network issues due to a power outage

25 Jun 2021 12:17 -0400

An overnight power outage (24-25 June 2021) appears to have resulted in some network issues. Functionality such as integration with external services (e.g. ORCID and Google Cloud) may be affected. We are investigating! [UPDATE: the network has been restored.]

PhysioNet/Computing in Cardiology Challenge 2021 accepted abstracts

23 Jun 2021 01:00 -0400

June 23, 2021: CinC has released its abstract decisions for the Challenge track of the conference. Congratulations to those with accepted abstracts. Those without an accepted abstract can still compete for a wildcard entry as outlined here.

Announcing the integration of PhysioNet with ORCID

4 May 2021 12:22 -0400

We are pleased to announce the integration of PhysioNet with ORCID, the unique digital identifier for researchers. Adding your ORCID iD to PhysioNet will help you to connect professional works — datasets, software, etc. — to your public ORCID profile.

If you are applying for "credentialed" access to PhysioNet resources, we highly recommend linking your ORCID iD to your profile prior to submitting the application. Doing so makes it easier for us to establish your identity, helping to expedite the review process.

In the future, we will be adding new features to enhance the ORCID integration, for example syncing your PhysioNet publications with your ORCID profile. Please let us know if you have suggestions for additional improvements at contact@physionet.org.

Head to https://physionet.org/settings/orcid/ to link your ORCID iD to PhysioNet.

The official phase of the PhysioNet/Computing in Cardiology Challenge 2021 has reopened

1 May 2021 01:00 -0400

May 1, 2021: The official phase of the Challenge reopens today. Due to your engagement, we have enormously expanded the training data, modified the lead combination, and modified the example code and scoring function. Please see our announcement on the Challenge forum for more details. We will update and clarify these changes in response to your questions in the coming days.

CinC deadline for the PhysioNet/Computing in Cardiology Challenge 2021 extended

19 Apr 2021 01:00 -0400

April 19, 2021: CinC has extended its abstract submission deadline to April 24, 2021. Please submit your abstract if you have not done so already. Like last year, CinC will host a hybrid conference with both in-person and remote attendance. Please see our announcement on the Challenge forum for more details.

PhysioNet/Computing in Cardiology Challenge 2021 submissions are due soon

13 Apr 2021 01:00 -0400

April 13, 2021: Only two days left to submit an abstract to CinC! Please find the abstract submission announcement and the instructions announcement on the Challenge forum. Please see the leaderboard for the final scores of the unofficial phase, and please submit your abstract today!

Leaderboard for the PhysioNet/Computing in Cardiology Challenge 2021 is available

24 Feb 2021 00:00 -0500

February 24, 2021: The leaderboard is now live! Please see the announcement on the Challenge forum. Please see the timing and priority of entries section here regarding the number of submissions allowed per day, so please submit early!

A tribute to George Moody

15 Feb 2021 17:18 -0500

We are deeply saddened to announce the passing of George Moody, one of the original PhysioNet team. George passed away as a consequence of COVID-19 on February 13, 2021, surrounded by his family, Edna, Benjamin, Jeremy and Melissa.

George has been a fundamental part of PhysioNet since the beginning, stretching back into the late 70s and early 1980's. George developed the WFDB libraries, and much of code that can be found on PhysioNet today, which underpins the Research Resource for Complex Physiologic Signals, and the fundamentals of ECG signal processing. George's work spanned state-of-the-art QRS detection, beat classification, noise assessment, and heart rate variability, among other areas. A pioneer and stalwart of open source principles, his work has blazed a trail in the field of physiological signal processing. This was acknowledged in 2016 by the AAMI, which awarded him (jointly with Ary Goldberger and Roger Mark) its most prestigious prize, the Laufman-Greatbatch Award.

George is perhaps best known for his design and implementation of the PhysioNet/CinC Challenges, which he ran for 15 years, from inception in 2000, until 2014, after which he retired due to ill health. These Challenges have pushed the field forward, stimulating research and translation, long before most, if not all, other public data science competitions began.

George was generous with his time and took pride in answering almost every email he received. He tirelessly devoted himself to the field, supporting everyone, from the newest student, to the giants of industry. At Computing in Cardiology, which he attended every year from 1979 to 2014, he was often the star of the show, generating a unique buzz around the Challenges. He also served on the board of the conference for longer than anyone, and was an active member of that community for over 30 years, contributing over 70 articles to the proceedings.

George began his career as an undergraduate at MIT, studying physics. His (sometimes supernatural) skill at C coding led him to work on the seminal MIT-BIH Arrhythmia Database with Roger Mark and Ary Goldberger. Still today, this database is at the core of many FDA applications. After his student days George became a research scientist at MIT in Roger Mark's group and remained there until retirement. George was a polymath. You could talk to him about any subject and realize his depth of thought was exceptional. There wasn't a subject on which he couldn't offer a genuinely deep and informed opinion. Yet he listened to everyone and treated all ideas and views with the utmost respect.

George was a man who appreciated life to its fullest. Perhaps his most impressive characteristic was that he always put his family first. A wonderful father and husband, he always made time for those he loved. Edna mentioned that George's favorite charity was Partners In Health (pih.org), and requested that anyone wishing to make a gesture in remembrance of him, to please direct it there. George was loved by us all, and we miss him enormously. He leaves an enduring legacy for the next generation, although he would be too humble to ever acknowledge that fact.

Accepting submissions for the PhysioNet/Computing in Cardiology Challenge 2021

30 Jan 2021 00:00 -0500

January 30, 2021: We are now accepting submissions for the 2021 Challenge! See below for details. Please register your team (even if you registered last year), check the submission instructions, and submit your code when ready. As always, please join the Challenge forum to discuss this year’s Challenge.

The PhysioNet/Computing in Cardiology Challenge 2021 is now open

24 Dec 2020 00:00 -0500

December 24, 2020: The NIH-funded 2021 Challenge is now open! See below for details. Please read this website for details and share questions and comments on Challenge forum. This year’s Challenge is generously co-sponsored by Google, MathWorks, and the Gordon and Betty Moore Foundation.

New applications for credentialed access to PhysioNet have been paused until January

17 Dec 2020 11:36 -0500

We have taken the difficult decision to pause all new applications for credentialed access to PhysioNet until 4th January 2021. We apologize for this inconvenience and we will be working hard to clear the backlog of applications in time for opening again in the New Year. Over the coming months, we will also be implementing changes to PhysioNet that we hope will streamline the process for future applications.

PhysioNet/Computing in Cardiology Challenge 2020 paper published

11 Nov 2020 00:00 -0500

The Organizers of the 2020 PhysioNet Challenge have published a paper describing Challenge. The paper is now available at Physiological Measurement as part of the focus issue on multilead ECG classification. Please cite this paper to describe the Challenge, consider submitting your work to the focus issue, and stay tuned for the launch of next year’s Challenge!

Computing in Cardiology 2020 proceedings will appear on the IEEE website

18 Oct 2020 01:00 -0400

The conference papers for Computing in Cardiology 2020 will appear on the CinC and IEEE websites.

Computing in Cardiology 2020 proceedings

28 Sep 2020 01:00 -0400

The organizers of the 2020 PhysioNet Challenge have submitted their paper to Physiological Measurement for review. Please cite Perez Alday EA, Gu A, J Shah A, Robichaux C, Ian Wong AK, Liu C, Liu F, Bahrami Rad A, Elola A, Seyedi S, Li Q, Sharma A, Clifford GD^* Reyna MA^*. Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020. Physiol. Meas. 2021 Jan 1;41(12):124003. doi: 10.1088/1361-6579/abc960 to refer to this year’s Challenge.

Physiological Measurement special issue

24 Sep 2020 01:00 -0400

The focus issue in Physiological Measurement is now open for submissions! To submit, create an account and choose “Special Issue Article” and then “Classification of Multilead ECGs”. Please do not use the phrases “PhysioNet Challenge”, “Computing in Cardiology”, or “classification of multilead ECGs” in your title, which should be specific to your contributions.

Winners of the PhysioNet/Computing in Cardiology Challenge 2020 announced

21 Sep 2020 01:00 -0400

The winners of the 2020 Challenge were announced at CinC in Rimini, Italy on September 16. From 1395 entries (707 successful) by 217 teams, 110 abstracts were accepted for presentation and 41 teams were officially ranked. Results can be found here.

Official phase of the PhysioNet/Computing in Cardiology Challenge 2020 now over

24 Aug 2020 01:00 -0400

The official phase of the Challenge is now over. We will contact teams scores for recent entries over the next few days, and we encourage teams to choose their favorite entry for evaluation on the full test set. Please see the full announcement on the Challenge forum for details, including important information about preparing for CinC.

MIMIC-IV is now available!

17 Aug 2020 14:15 -0400

We are delighted to announce that MIMIC-IV has been published on PhysioNet! MIMIC-IV, the latest version of MIMIC, is a database comprising comprehensive clinical information on hospital stays for patients admitted to a tertiary academic medical center in Boston, MA, USA.

Major changes from MIMIC-III include: (1) a modular structure that links core hospital data to multiple data sources, including chest x-ray images; (2) an approach to date shifting that provides approximate year of admission; (3) new sources of data; such as the electronic medicine administration record.

The dataset is available from PhysioNet, and access is managed in the same way as MIMIC-III. If you already have access to MIMIC-III, then you will be granted access after signing the Data Use Agreement in the "Files" section of the project. New users will need to complete the credentialing process first (see: https://mimic-iv.mit.edu/docs/access/ for more details). For detailed guidelines on using MIMIC-IV, see the documentation!

Opportunity to join the PhysioNet team [Update: this position is no longer available.]

11 Aug 2020 13:25 -0400

The MIT Laboratory for Computational Physiology is seeking a Post-Doctoral Associate to conduct independent research in health care informatics. The Laboratory is an NIH-supported multi-disciplinary group of clinicians, data scientists and engineers that produced the publicly distributed and growing MIMIC database. It is a rich and open research resource that supports signal processing and machine learning research leading to new knowledge and patient-specific prognostic and therapeutic guidance for critical care.

The Postdoc will contribute to the design and management of the current and future MIMIC databases, and will conduct multidisciplinary original research together with clinicians. The position provides the opportunity to interact with a world-class laboratory comprised of engineers, mathematicians and clinical staff working at the frontiers of translational medicine and advanced research in the domain of critical care informatics and machine learning. The Research Fellow will both contribute to ongoing research projects and propose innovative new projects suitable for research grant funding.

The ideal candidate has a doctoral degree in science or engineering, or a related discipline to assure high level understanding of the research environment. Experience in relational database development and administration is important, ideally in a medical environment. Competence and experience in a subset of the following is expected: Linux, Python, data management. Knowledge of medical terminology is desirable. Strong interpersonal and communication skills are essential. [Update: this position is no longer available.]

Teams invited to join the PhysioNet/Computing in Cardiology Challenge 2020

29 Jul 2020 01:00 -0400

We have invited two “wild card” teams to the 2020 PhysioNet Challenge and increased the resources available for training your models.

Now accepting entries for the official phase of the PhysioNet/Computing in Cardiology Challenge 2020

1 Jul 2020 01:00 -0400

We are now accepting entries for the official phase of the Challenge. For the first time, we are requiring teams to submit their pretrained models and code for training their models. See the full announcement on the Challenge forum and the previous two announcements for details.

Updated SNOMED-CT mapping posted for the PhysioNet/Computing in Cardiology Challenge 2020

24 Jun 2020 01:00 -0400

We have posted an updated SNOMED CT code mapping here and here and an updated scoring metric in Python here. See the full announcement on the Challenge forum for details.

Additional data released for the PhysioNet/Computing in Cardiology Challenge 2020

8 Jun 2020 01:00 -0400

We are releasing 4 new tranches of 12-lead ECGs with SNOMED-CT labels to complement the 2 previously released tranches. Altogether, 6 databases with 43,101 labeled recordings are now available. We will reopen the scoring system and release an updated scoring metric in the coming days. See the full on the Challenge forum for details.

New on PhysioNet: the HiRID critical care dataset

5 Jun 2020 12:29 -0400

We are pleased to announce the release of the HiRID critical care dataset, developed as part of a collaboration between Bern University Hospital and the Swiss Federal Institute of Technology (ETH). HiRID is a freely accessible critical care dataset containing data relating to more than 33 thousand admissions to the Department of Intensive Care Medicine of the Bern University Hospital, Switzerland, an interdisciplinary 60-bed unit admitting >6,500 patients per year.

Acceptances announced for the PhysioNet/Computing in Cardiology Challenge 2020

3 Jun 2020 01:00 -0400

All abstract acceptances and rejections have been announced. Please check the Google Group announcement for more details.

Diagnoses posted for the PhysioNet/Computing in Cardiology Challenge 2020

27 May 2020 01:00 -0400

The full list of diagnoses for the Challenge have now been posted here. See the full announcement on the Challenge Google Group here.

Review complete for the PhysioNet/Computing in Cardiology Challenge 2020 abstracts

26 May 2020 01:00 -0400

Abstract reviews are now complete and will be announced within the next week. Please see the updated key dates/deadlines and details on the wild card entries below. See the full announcement on the Challenge Google Group here.

Abstracts are under review for the PhysioNet/Computing in Cardiology Challenge 2020

12 May 2020 01:00 -0400

Your abstracts are under review, and we hope to release acceptances and rejections by early June. For those who missed the abstract deadline, we will provide an opportunity to qualify as a wild card participant over the summer, so please don’t give up!

New data for the PhysioNet/Computing in Cardiology Challenge 2020

11 May 2020 01:00 -0400

We have begun the official phase of the Challenge. Please find a new tranche of data with SNOMED-CT codes as diagnoses. Please note that there are some errors or debatable labels in some of the data. Part of the Challenge will be working out how to deal with these issues. In the next few weeks, we will release more data and reopen the scoring system with a new scoring metric.

Submission system reopened for the PhysioNet/Computing in Cardiology Challenge 2020

25 Apr 2020 01:00 -0400

We have reopened the submission system for 5 more days (until 30 April 2020 at 23:59 GMT) to help teams who are able to submit bug-free entries qualify for the Challenge.

Computing in Cardiology abstract deadline extended

31 Mar 2020 01:00 -0400

The Computing in Cardiology abstract deadline has been extended to May 1

Significant delays are expected to applications for credentialed access to PhysioNet.

25 Mar 2020 20:43 -0400

We are currently dealing with a high volume of applications for credentialed access to PhysioNet, so please expect significant delays in the review process. We are doing our best to deal with the waitlist quickly, handling applications in the order in which they are received. To help ensure that your application is successful, please remember to:

Include a copy of your CITI training report (not the certificate).
Remind your reference to reply promptly when contacted.
Check your application details are correct before submitting.

We apologize for the inconvenience. Please bear with us during this busy time!

PhysioNet/Computing in Cardiology Challenge 2020 leaderboard

16 Mar 2020 01:00 -0400

The leaderboard is now live.

Congratulations to the winners of the 2020 WiDS Challenge

2 Mar 2020 11:55 -0500

Congratulations to the winners of the 2020 Women in Data Science (WiDS) Challenge. The event attracted 951 teams from over 80 countries who competed on models to predict the outcome of critically ill patients. The dataset used in the study, sourced from the GOSSIS (Global Open Source Severity of Illness Score) Consortium, comprised detailed information on over 130,000 ICU stays. For updates on future challenges by WiDS, subscribe to the WiDS mailing list.

Announcing the PhysioNet/Computing in Cardiology Challenge 2020 on Classification of 12-lead ECGs

10 Feb 2020 17:09 -0500

We are delighted to announce the PhysioNet/Computing in Cardiology Challenge 2020 on Classification of 12-lead ECGs. For more information, see the Challenge website: https://physionet.org/content/challenge-2020/

Quick links for this year's Challenge can be found here:

Registration form: https://bit.ly/37d21iN
Public discussion forum: https://groups.google.com/forum/#!forum/physionet-challenges
Rules and deadlines: https://physionetchallenges.github.io/2020/#rules-and-deadlines

More information will be posted on the website linked above (and eventually mirrored on physionet.org/challenge/2020 with a delay as it is available). Please check the Challenge forum for real time updates. Please also post questions and comments in the forum. However, if your question reveals information about your entry, then please email challenge [at] physionet.org. We may post parts of our reply publicly if we feel that all Challengers should benefit from the information contained in our responses. We will not answer emails about the Challenge to any other address.

Many thanks again for your continued support of this event and we hope you enjoy this year's challenge.

MIMIC-CXR paper published!

10 Feb 2020 16:06 -0500

A journal article describing the MIMIC-CXR database was recently published in Scientific Data. The article provides detail regarding the collection, curation, and processing done in order to create the database. The article is open access and available online [1].

The database has also been preprocessed into compressed JPG format images, which have been made available on PhysioNet as the MIMIC-CXR-JPG Database. The database includes labels extracted from the free-text reports using publicly available tools. You can read more about the creation of this resource in our arXiv preprint [2].

Finally, we have created the mimic-cxr GitHub repository for collaborative code development on MIMIC-CXR [3]. The code used to generate MIMIC-CXR-JPG from MIMIC-CXR is available in the repository already. We welcome code contributions from all users, and we encourage discussion of the data via the GitHub issues.

[1] Johnson AE, Pollard TJ, Berkowitz SJ, Greenbaum NR, Lungren MP, Deng CY, Mark RG, Horng S. MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports. Scientific Data. 2019;6.

[2] Johnson AE, Pollard TJ, Greenbaum NR, Lungren MP, Deng C-Y, Peng Y, Lu Z, Mark RG, Berkowitz SJ, Horng S. MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs. arXiv preprint arXiv:1901.07042. 2019.

[3] https://github.com/MIT-LCP/mimic-cxr

PhysioNet/Computing in Cardiology Challenge 2020 now open

7 Feb 2020 00:00 -0500

The 2020 Challenge is now open!

WiDS (Women in Data Science) Challenge Announced! Register your team by 24 February 2020

23 Jan 2020 14:18 -0500

The WiDS Datathon 2020 focuses on patient health through data from MIT’s GOSSIS (Global Open Source Severity of Illness Score) initiative. Brought to you by the Global WiDS team, the West Big Data Innovation Hub, and the WiDS Datathon Committee. Winners will be announced at the WiDS Conference at Stanford University and via livestream, reaching a community of 100,000+ data enthusiasts across more than 50 countries.

Opportunity for a Research Software Engineer to join the PhysioNet team

21 Nov 2019 16:00 -0500

The MIT Laboratory for Computational Physiology is seeking a Research Software Engineer to support and undertake projects focused on improving patient care. Joining a team of data scientists and clinicians, the Engineer will help to manage the system network, write code for research studies, and initiate and develop research software.

The position would be a good fit for someone with a bachelor’s or master’s degree in a technical subject such as biomedical engineering, physics, computer science, or equivalent experience. For more details, please see the job posting on the MIT website or contact us directly if you have questions.

Community forum for the 2019 PhysioNet/CinC Challenge

5 Nov 2019 12:51 -0500

If you have any questions or comments regarding this challenge, please post it directly in our Community Discussion Forum. This will increase transparency (benefiting all the competitors) and ensure that all the challenge organizers see your question.

Official paper describing the 2019 PhysioNet Challenge

4 Nov 2019 16:45 -0500

The official paper describing the 2019 PhysioNet Challenge will appear in Critical Care Medicine.

MIMIC-III available on the cloud

30 Sep 2019 14:28 -0400

The MIMIC-III database is now available on two major cloud platforms: Google Cloud Platform (GCP) and Amazon Web Services (AWS). To access the data on the cloud, simply add the relevant cloud identifier to your PhysioNet profile. Further instructions are available on the MIMIC-III website.

Tutorials are available for using MIMIC-III with BigQuery (GCP) and using MIMIC-III with Athena (AWS).

MIMIC-CXR Database v2.0.0 now available!

27 Sep 2019 13:11 -0400

The MIMIC-CXR Database has been updated to v2.0.0. The database now contains DICOM format image files and free-text radiology reports. All data has been de-identified.

Credentialed users can access the data after signing the data use agreement.

Some users may have preferred the JPG format images for convenience, despite the information loss when storing the images in this format. We plan to release a distinct project on PhysioNet which contains the same images as MIMIC-CXR but in JPG format. This distinct project will also contain structured labels derived from the radiology report. Stay tuned!

Official results for the 2019 PhysioNet Challenge

17 Sep 2019 15:31 -0400

Official results for the 2019 Challenge and Hackathon are now available.

Pre-conference hackathon at Computing in Cardiology 2019

8 Jul 2019 20:00 -0400

Thanks to our sponsors, a pre-conference hackathon (with prize(s)) will take place on Sunday 8th September in Singapore. Registration is required. Rules and more information can be found here .

"Wild card" teams approved for the 2019 PhysioNet Challenge

23 Jun 2019 20:00 -0400

Two "wild card" teams were approved for inclusion in the Challenge. We are looking forward to meeting them in Singapore!

Google Cloud credits for the PhysioNet Challenge

28 May 2019 20:00 -0400

We are accepting requests for Google Cloud Credits ($500 per eligible team). Requests are due by 29 May, 2019. Please see here for more information on how to apply for them. Requests will be processed in order and sent on to Google. We cannot guarantee you will receive them, especially later in the competition.

Notices of acceptance have been sent for CinC abstracts

24 May 2019 20:00 -0400

By now you should have received your acceptance or rejection notices for your abstracts. If you were rejected, please do not worry - there are two more options to compete. See here and here for more information on this.
We have added a `wild card' entry to allow one more team to enter the competition and be eligible for all the prizes. See here for more information on this.
There will be an on-site hackathon revisiting the Challenge (with a separate award) on Sunday 8th September, before the conference begins in Singapore. Any team (whether previously registered for the Challenge or not) with at least one attendee at the conference, who turns up in person to register for the Hackathon, is eligible to enter. See here for more information on this.

Scoring for the PhysioNet Challenge

2 May 2019 20:00 -0400

Please check the leaderboard for the current Challenge scores.

Now accepting Challenge submissions

25 Apr 2019 20:00 -0400

We are now accepting submissions for the official phase of the Challenge.
Please check the submission instructions for information about how to submit your entry and a FAQ with common submission issues.
When ready, please submit your entry here.

Official phase of the 20th PhysioNet/Computing in Cardiology Challenge is now open.

22 Apr 2019 20:00 -0400

We have made several changes from the unofficial phase of the Challenge (see below). We invite comments and questions about these changes. We plan to accept submissions again on Thursday, 25 April at 12:01 am GMT.
We will only use our new cloud submission system for the official phase of the Challenge. See the updated instructions (here) for details. The past submission system is no longer available.
We ask participants to write causal algorithms that make predictions using current and past (but not future) information. See the submission instructions and sample prediction code (here) for details.
Note that you will have 10 submissions in this official phase. We will score your results on a subset of the test data. At the end of the competition we will ask you to nominate your 'best' algorithm (it need not be the one that gave you the best score) and we will run it on the full test data to provide the final test score.
Please do not submit all ten entries in the last week of the competition. Even though we can scale the computing, failures require manual intervention and feedback. We can't do this for 1000+ entries in the final week.
Also - we will be offering up to $500 in Google Cloud credits (courtesy of the Google Cloud Team) to the best performing entries by June, so it's worth getting a good score before then!

Your feedback on physionet.org

22 Apr 2019 16:09 -0400

The new PhysioNet website is intended to simplify the process of finding and reusing data. Key improvements include:

an updated search tool for finding data and software
a new registration system
a simplified process for sharing your data and software

We welcome your feedback! Please send us your comments using our feedback form.

Your ideas and suggestions will be used for continuous improvement.

Cloud submission system for the 2019 PhysioNet Challenge

11 Apr 2019 20:00 -0400

We have now implemented a cloud submission system. Instructions for the cloud submission system available here.
The deadline of the unofficial phase of the competition has been extended to 11.59pm GMT on Sunday 14th April 2019. This will give you enough time to receive scores and, very importantly, submit abstracts to cinc.org before the 15th. Please see here for important hints on how to prepare a successful abstract, even if you don't receive a score.
If you don't receive a score - don't panic - just submit an abstract to cinc.org by the deadline on the 15th April with some results - cross validated on the training data.
The hiatus has now been moved, and starts on the 15th April and lasts until 12 midnight GMT on the 21st April. The Challenge re-opens at 12.01 am GMT on the 22 April.

Deadline extended for the 2019 PhysioNet Challenge

8 Apr 2019 20:00 -0400

The entry submission system is available here.
The deadline of the unofficial phase of the competition has been extended to 11.59pm GMT on Wednesday 10th April 2019.