Resources


Database Credentialed Access

TherLid: A Thermometry Linked Dataset

Jeremy Tan, Inês Martins, João Matos, et al.

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.

thermometry intensive care unit health equity electronic health records

Published: Jan. 21, 2025. Version: 1.0.0

Database Credentialed Access

Medical-CXR-VQA dataset: A Large-Scale LLM-Enhanced Medical Dataset for Visual Question Answering on Chest X-Ray Images

Xinyue Hu, Lin Gu, Kazuma Kobayashi, et al.

Medical-CXR-VQA provides a large-scale LLM-enhanced dataset for visual question answering in medical chest x-ray images.

Published: Jan. 21, 2025. Version: 1.0.0

Database Credentialed Access

MS-CXR: Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, et al.

MS-CXR is a new dataset containing 1162 chest X-ray bounding box labels paired with radiology text descriptions, annotated and verified by two board-certified radiologists.

vision-language processing chest x-ray phrase grounding localization

Published: Nov. 15, 2024. Version: 1.1.0

Database Credentialed Access

RadGraph2: Tracking Findings Over Time in Radiology Reports

Adam Dejl, Sameer Khanna, Patricia Therese Pile, et al.

RadGraph2 is a dataset of 800 chest radiology reports annotated using a fine-grained entity-relationship schema, which captures key findings as well as mentions of changes that occurred in comparison with the previous radiology studies.

chest x-rays relation extraction disease progression information extraction radiology reports named entity recognition

Published: Aug. 8, 2024. Version: 1.0.0

Database Credentialed Access

EHRNoteQA: An LLM Benchmark for Real-World Clinical Practice Using Discharge Summaries

Sunjun Kweon, Jiyoun Kim, Heeyoung Kwak, et al.

An LLM Benchmark for Real-World Clinical Practice Using Discharge Summaries

Published: June 26, 2024. Version: 1.0.1

Database Credentialed Access

EHR-DS-QA: A Synthetic QA Dataset Derived from Medical Discharge Summaries for Enhanced Medical Information Retrieval Systems

Konstantin Kotschenreuther

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

mimic-iv clinical question-answering medical discharge summaries large language models

Published: Jan. 11, 2024. Version: 1.0.0

Model Credentialed Access

Characterization of Stigmatizing Language in Medical Records

Keith Harrigian, Ayah Zirikly, Brant Chee, et al.

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

clinical natural language processing domain transfer bias stigmatizing language mimic large language models

Published: Nov. 6, 2023. Version: 1.0.0

Database Credentialed Access

Radiology Report Expert Evaluation (ReXVal) Dataset

Feiyang Yu, Mark Endo, Rayan Krishnan, et al.

The Radiology Report Expert Evaluation (ReXVal) Dataset is a publicly available dataset of radiologist evaluations of errors in automatically generated radiology reports.

Published: June 20, 2023. Version: 1.0.0

Database Credentialed Access

Tasks 1 and 3 from Progress Note Understanding Suite of Tasks: SOAP Note Tagging and Problem List Summarization

Yanjun Gao, John Caskey, Timothy Miller, et al.

We introduce a hierarchical annotation suite of tasks addressing clinical text understanding, reasoning and abstraction over evidence, and diagnosis summarization. One task is section tagging major section and the other task is diagnosis generation.

Published: Sept. 30, 2022. Version: 1.0.0

Database Credentialed Access

Learning to Ask Like a Physician: a Discharge Summary Clinical Questions (DiSCQ) Dataset

Eric Lehman

Dataset of questions asked by medical experts about patients. Medical experts will read a discharge summary line-by-line and (1) ask any question that they may have and (2) record what in the text "triggered" them to ask their question.

question generation question answering machine learning

Published: July 28, 2022. Version: 1.0