Resources

22 results for "medical ai"

Database Credentialed Access

Chest X-ray segmentation images based on MIMIC-CXR

Li-Ching Chen, Po-Chih Kuo, Ryan Wang, et al.

As more and more artificial intelligence (AI) or deep learning technologies have been applied to medical image applications such as radiological finding identification in chest X-rays (CXRs), the interpretability of the prediction model is crucial f…
Published: Aug. 18, 2022. Version: 1.0.0
Database Credentialed Access

RaDialog Instruct Dataset

Chantal Pellegrini, Ege Özsoy, Benjamin Busam, et al.

Conversational AI tools that can generate and discuss clinically correct radiology reports for a given medical image have the potential to transform radiology. Such a human-in-the-loop radiology assistant could facilitate a collaborative diagnostic …
Published: July 12, 2024. Version: 1.1.0
Database Credentialed Access

MIMIC-IV-Ext Triage Instruction Corpus

Qingyang Shen, Quan Guo

Emergency department (ED) overcrowding leads to delayed care, increased patient risk, and inefficient resource use. The MIMIC-IV-Ext Triage Instruction Corpus (MIETIC) addresses this by providing 9,629 structured triage cases from MIMIC-IV, aligned …
Published: March 4, 2025. Version: 1.0.0
Database Open Access

ReXErr-v1: Clinically Meaningful Chest X-Ray Report Errors Derived from MIMIC-CXR

Vishwanatha Rao, Serena Zhang, Julian Acosta, et al.

Interpreting medical images and writing radiology reports is a critical yet challenging task in healthcare. Despite their importance, both human-written and AI-generated reports are liable to errors, leaving a need for robust and representative data…
Published: March 19, 2025. Version: 1.0.0
Database Open Access

Heart and lung segmentations for MIMIC-CXR/MIMIC-CXR-JPG and Montgomery County TB databases

Benjamin Duvieusart, Felix Krones, Guy Parsons, et al.

Segmenting the heart and lungs from chest X-ray images is essential for accurate disease diagnosis, enabling the calculation of image-derived digital biomarkers for cardiopulmonary health assessment. Furthermore, creation of annotated data sets can …
Published: Aug. 14, 2023. Version: 1.0.0
Model Credentialed Access

Shareable Artificial Intelligence to Extract Cancer Outcomes from Electronic Health Records for Precision Oncology Research

Kenneth Kehl, Pavel Trukhanov, Christopher Fong, et al.

Databases that link molecular data to clinical outcomes can inform precision cancer research into novel prognostic and predictive biomarkers. However, outside of clinical trials, cancer outcomes are typically recorded only in text form within electr…
Published: Oct. 24, 2024. Version: 1.0.0
Database Credentialed Access

Embedding-Based Representations for BRSET and mBRSET

David Restrepo, Chenwei Wu, Michael Morley, et al.

BRSET and mBRSET are publicly available Brazilian ophthalmological datasets composed of curated retinal fundus photographs with associated clinical and demographic information. While these resources enable diverse research applications, training dee…
Published: March 30, 2026. Version: 1.0.0
Database Restricted Access

EchoNext: A Dataset for Detecting Echocardiogram-Confirmed Structural Heart Disease from ECGs

Pierre Elias, Joshua Finer

This dataset contains a de-identified collection of 100,000 12-lead electrocardiograms (ECGs) with paired structural heart disease (SHD) labels derived from echocardiography, collected at Columbia University Irving Medical Center. Each ECG is provid…
Published: April 30, 2026. Version: 1.1.1
Database Credentialed Access

MIMIC-IV-Ext-MDS-ED: Multimodal Decision Support in the Emergency Department - a Benchmark Dataset for Diagnoses and Deterioration Prediction in Emergency Medicine

Juan Miguel Lopez Alcaraz, Nils Strodthoff

Measurable progress in the development of medical decision support systems has been hindered by a lack of comprehensive datasets. Many available datasets focus on narrow prediction tasks and do not include a diverse range of data types, which limits…
Published: Sept. 12, 2024. Version: 1.0.0
Database Credentialed Access

RadVLM Instruction Dataset

Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruiperez-Campillo, et al.

We release the RadVLM instruction dataset, a large-scale resource used to train the RadVLM model on diverse radiology tasks. The dataset contains 1,115,021 image–instruction pairs spanning five task families: (i) report generation from frontal CXRs …
Published: Sept. 25, 2025. Version: 1.0.0