2020 News


The PhysioNet/Computing in Cardiology Challenge 2021 is now open

News from: Will Two Do? Varying Dimensions in Electrocardiography: The PhysioNet/Computing in Cardiology Challenge 2021 v1.0.2.

Dec. 24, 2020

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

Dec. 17, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

Nov. 11, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

Oct. 18, 2020

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

Computing in Cardiology 2020 proceedings

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

Sept. 28, 2020


Physiological Measurement special issue

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

Sept. 24, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

Sept. 21, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

Aug. 24, 2020

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!

Aug. 17, 2020

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.]

Aug. 11, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

July 29, 2020

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

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

July 1, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

June 24, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

June 8, 2020

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

June 5, 2020

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. 

Read more: https://physionet.org/content/hirid/


Acceptances announced for the PhysioNet/Computing in Cardiology Challenge 2020

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

June 3, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

May 27, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

May 26, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

May 12, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

May 11, 2020

We have begun the official phase of the Challenge. Please find a new tranche of data posted here 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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

April 25, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

March 31, 2020

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

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

March 25, 2020

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

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

March 16, 2020

The leaderboard is now live.

Congratulations to the winners of the 2020 WiDS Challenge

News from: WiDS (Women in Data Science) Datathon 2020: ICU Mortality Prediction v1.0.0.

March 2, 2020

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

Feb. 10, 2020

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://physionetchallenges.github.io/2020/

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

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. 

Read more: https://physionetchallenges.github.io/2020/


MIMIC-CXR paper published!

News from: MIMIC-CXR Database v2.0.0.

Feb. 10, 2020

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

Read more: https://www.nature.com/articles/s41597-019-0322-0


PhysioNet/Computing in Cardiology Challenge 2020 now open

News from: Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.1.

Feb. 7, 2020

The 2020 Challenge is now open!

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

News from: WiDS (Women in Data Science) Datathon 2020: ICU Mortality Prediction v1.0.0.

Jan. 23, 2020

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.

WiDS Challenge 2020

Read more: https://physionet.org/content/widsdatathon2020/1.0.0/