Resources

Image-based instruct data for Chest X-Ray understanding and analysis.

A suite of classifiers for detecting three types of stigmatizing language in electronic medical records. Trained on MIMIC-IV discharge notes.

A pressure and flow dataset was collected from a trial of 30 adults at the University of Canterbury undergoing CPAP therapy for a variety of instructed breath rates at PEEP levels of 4cmH2O and 7cmH2O.

This dataset includes bounding box-statement pairs for chest X-ray images, derived from radiologists’ eye-tracking data (for explainability) and annotations, for local visual-language models.

We present the Synthetic Mention Corpora for Disease Entity Recognition and Normalization, containing 128000 disease mentions from the UMLS disorder group, generated by an LLM. This corpus aims to improve these tasks in biomedical and clinical texts.

CheXmask Database is a 657,566 uniformly annotated chest radiographs with segmentation masks. Images were segmented using HybridGNet, with automatic quality control indicated by RCA scores.

TherLiD is an open-source dataset of 13,251 paired temperature readings (contact and infrared) from MIMIC-IV and eICU databases. With added demographics and derived data, it supports research on racial and ethnic disparities in infrared thermometry.

COVID Data for Shared Learning (CDSL) is a multimodal database comprising de-identified structured health data and radiological images from 4,479 patients with COVID-19, as a comprehensive toolkit for developing predictive models.

Holter ECG database from Japan, containing data from 100 unique patients with paroxysmal AF including expert annotations of Supraventricular arrhythmias at the beat level.

We introduce MIMIC-Ext-MIMIC-CXR-VQA, a complex, diverse, and large-scale dataset designed for Visual Question Answering (VQA) tasks within the medical domain, focusing primarily on chest radiographs.