Resources

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

Text-based Longitudinal Data for Predicting Nosocomial Disease Risk as used by CANTRIP.

Brazilian clinical dataset containing over 70,000 admissions from 10 hospitals in two Brazilian states.

PIC (Paediatric Intensive Care) is a large paediatric-specific, single-centre, bilingual database comprising information relating to children admitted to critical care units at a large children’s hospital in China.

MIMIC-III is a large, freely-available database comprising deidentified health-related data associated with over forty thousand patients who stayed in critical care units of the Beth Israel Deaconess Medical Center between 2001 and 2012. The databas…

Dataset consisting of question and answer pairs synthetically generated from medical discharge summaries, designed to facilitate the training and development of large language models specifically tailored for healthcare applications

Dataset consisting of question and answer pairs synthetically generated from medical discharge summaries, designed to facilitate the training and development of large language models specifically tailored for healthcare applications

A clinician-labeled dataset for fact-checking long-form clinical text against patient EHRs. The dataset contains LLM-written and human-written Brief Hospital Course summaries decomposed to atomic claim and sentence propositions with annotations.

This dataset presents a collection of preprocessed and labeled clinical notes derived from "MIMIC-IV-Note", and aims to facilitate the development of ML models focused on summarizing brief hospital courses (BHC) from clinical notes.

CXRGraph is a structured radiology report dataset built upon RadGraph and tailored for the Automatic Radiology Report Generation task. It can identify more task-relevant information such as abnormalities and hallucinated prior references.