Resources


Database Open Access

Eye Tracking Dataset for the 12-Lead Electrocardiogram Interpretation of Medical Practitioners and Students

Mohammed Tahri Sqalli, Dena Al-Thani, Mohamed Elshazly, et al.

The project aims at collecting a dataset using eye-tracking technology to understand the 12-lead electrocardiogram interpretation visual behavior for medical practitioners and students with different expertise levels.

human vision medical students ecg interpretation medical image interpretation medical practice medical education human-computer interaction medical practitioners visual expertise eye-tracking ecg electrocardiogram

Published: March 16, 2022. Version: 1.0.0

Database Open Access

Eye Tracking Dataset for the 12-Lead Electrocardiogram Interpretation of Medical Practitioners and Students

Mohammed Tahri Sqalli, Dena Al-Thani, Mohamed Elshazly, et al.

The project aims at collecting a dataset using eye-tracking technology to understand the 12-lead electrocardiogram interpretation visual behavior for medical practitioners and students with different expertise levels.

human vision medical students ecg interpretation medical image interpretation medical practice medical education human-computer interaction medical practitioners visual expertise eye-tracking ecg electrocardiogram

Published: March 16, 2022. Version: 1.0.0

Database Open Access

Eye Tracking Dataset for the 12-Lead Electrocardiogram Interpretation of Medical Practitioners and Students

Mohammed Tahri Sqalli, Dena Al-Thani, Mohamed Elshazly, et al.

The project aims at collecting a dataset using eye-tracking technology to understand the 12-lead electrocardiogram interpretation visual behavior for medical practitioners and students with different expertise levels.

human vision medical students ecg interpretation medical image interpretation medical practice medical education human-computer interaction medical practitioners visual expertise eye-tracking ecg electrocardiogram

Published: March 16, 2022. 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.

Chest X-Ray reports containing synthetic errors based upon the MIMIC-CXR database. Errors were injected using LLMs and sampled across common human and AI model errors.

Published: March 19, 2025. Version: 1.0.0

Database Credentialed Access

Chest X-ray segmentation images based on MIMIC-CXR

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

A chest x-rays segmentation dataset derived from MIMIC-CXR based on deep learning algorithm and human examination.

segmentation chest x-rays cxr

Published: Aug. 18, 2022. Version: 1.0.0