Resources

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

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.

Annotations of ten types of medical decisions from discharge summaries in the MIMIC-III database.

Medical oncology progress notes annotated with advanced, comprehensive oncology-relevant concepts and relationships.

RadCoref is a small subset of MIMIC-CXR with manually annotated coreference mentions and clusters. Based on the annotated data, we fine-tuned a deep neural model and used it to annotate the whole MIMIC-CXR dataset. Both data are available.

Annotation dataset of social determinants of health from MIMC-III Clinical Care Database notes.

This is the data storage for BioNLP Workshop Shared Task 1A: Problem List Summarization.

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