Resources


Challenge Open Access

QT Interval Measurement: The PhysioNet/Computing in Cardiology Challenge 2006

The seventh annual PhysioNet/Computers in Cardiology Challenge addresses a question of high clinical interest: Can the QT interval be measured by fully automated methods with an accuracy acceptable for clinical evaluations?

challenge ecg

Published: Nov. 1, 2006. Version: 1.0.0

Software Open Access

EVAL_ST Tool

The EVAL_ST tool is an open source tool to evaluate and compare performance and robustness of ST episode detection algorithms. The tool supports all standard and other relevant performance measures, aggregate gross and average statistics, and bootst…

arrhythmia

Published: Sept. 17, 2004. Version: 1.0.0

Database Open Access

Long Term ST Database

The Long-Term ST Database contains 86 lengthy ECG recordings of 80 human subjects, chosen to exhibit a variety of events of ST segment changes, including ischemic ST episodes, axis-related non-ischemic ST episodes, episodes of slow ST level drift, a…

ecg

Published: Nov. 29, 2000. Version: 1.0.0

Visualize waveforms

Database Open Access

MIT-BIH Polysomnographic Database

Recordings of multiple physiologic signals during sleep, collected from 18 subjects monitored at Boston's Beth Israel Hospital Sleep Laboratory.

apnea sleep eeg multiparameter respiration ecg

Published: Aug. 3, 1999. Version: 1.0.0

Visualize waveforms

Database Credentialed Access

EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, Jungwoo Oh, Lei JI, Eric Chang, Tackeun Kim, Edward Choi

We present EHRXQA, the first multi-modal EHR QA dataset combining structured patient records with aligned chest X-ray images. EHRXQA contains a comprehensive set of QA pairs covering image-related, table-related, and image+table-related questions.

question answering chest x-ray benchmark evaluation multi-modal question answering ehr question answering semantic parsing machine learning deep learning electronic health records visual question answering

Published: July 23, 2024. Version: 1.0.0

Database Credentialed Access

EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, Jungwoo Oh, Lei JI, Eric Chang, Tackeun Kim, Edward Choi

We present EHRXQA, the first multi-modal EHR QA dataset combining structured patient records with aligned chest X-ray images. EHRXQA contains a comprehensive set of QA pairs covering image-related, table-related, and image+table-related questions.

question answering chest x-ray benchmark evaluation multi-modal question answering ehr question answering semantic parsing machine learning deep learning electronic health records visual question answering

Published: July 23, 2024. Version: 1.0.0