Resources


Challenge Credentialed Access

ShAReCLEF eHealth 2013: Natural Language Processing and Information Retrieval for Clinical Care

Danielle Mowery

2013 ShARe/CLEF eHealth Evaluation Lab: Natural Language Processing and Information Retrieval for Clinical Care (Tasks 1 and 2).

natural language processing

Published: Feb. 15, 2013. Version: 1.0

Database Contributor Review

BRATECA (Brazilian Tertiary Care Dataset): a Clinical Information Dataset for the Portuguese Language

Henrique Dias, Ana Helena Dias Pereira dos Ulbrich

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

prescriptions exams tertiary care natural language processing clinical notes

Published: July 14, 2022. Version: 1.1

Database Credentialed Access

Medical Expert Annotations of Unsupported Facts in Doctor-Written and LLM-Generated Patient Summaries

Stefan Hegselmann, Shannon Shen, Florian Gierse, et al.

Annotations for unsupported facts in 100 original MIMIC patient summaries (discharge instructions) and hallucinations in 100 Large Language Model (LLM) generated patient summaries labeled by two medical experts.

Published: April 30, 2025. Version: 1.0.1

Challenge Credentialed Access

ShAReCLEF eHealth Evaluation Lab 2014 (Task 2): Disorder Attributes in Clinical Reports

Danielle Mowery

The ShARe/CLEF eHealth 2014 Challenge (Task 2) on Disorder Attributes in Clinical Reports

Published: Nov. 1, 2013. Version: 1.0

Database Credentialed Access

MIMIC-IV-Ext clinical decision support for referral, triage and diagnosis

Farieda Gaber, Altuna Akalin

This MIMIC-IV extended dataset is designed to evaluate and improve LLMs' ability to assist with triage, specialist referral, and diagnosis, using critical patient information such as history of present illness,vitals signs and other relevant data.

Published: Oct. 8, 2025. Version: 1.0.2

Database Credentialed Access

MIMIC-III-Ext-VeriFact-BHC: Labeled Propositions From Brief Hospital Course Summaries for Long-form Clinical Text Evaluation

Philip Chung, Akshay Swaminathan, Alex Goodell, et al.

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.

natural language processing clinical informatics formal logic chart review clinical notes text embedding electronic health records artificial intelligence brief hospital course long-form text llm evaluation logical atomism retrieval-augmented generation text reranking clinical medicine atomic claim fact verification hybrid retrieval llm-as-a-judge large language models

Published: Aug. 27, 2026. Version: 1.1.0

Database Credentialed Access

C-REACT: Contextualized Race and Ethnicity Annotations for Clinical Text

Oliver Bear Don't Walk IV, Adrienne Pichon, Harry Reyes Nieva, et al.

Two sets of gold-standard annotations for race and ethnicity information from clinical notes in MIMIC-III. Contains race and ethnicity label assignments and related information such as country of origin and spoken language.

patient country information race and ethnicity patient language information clinical notes

Published: Oct. 21, 2024. Version: 1.0.0

Database Credentialed Access

AIPatient KG: MIMIC-III and CORAL Electronic Health Records based Patient Knowledge Graph

Lizhou Fan, Huizi Yu

This project integrates MIMIC-III and CORAL electronic health records into knowledge graphs to improve medical analysis and enhance decision-making capabilities. Resources include two knowledge graph snapshots and two question-and-answering datasets.

Published: April 15, 2025. Version: 1.0.0

Model Credentialed Access

Clinical BERT Models Trained on Pseudo Re-identified MIMIC-III Notes

Eric Lehman, Sarthak Jain, Karl Pichotta, et al.

We explore recovering sensitive info from BERT trained over non-deidentified EHR. We make our models and data available to further facilitate research.

Published: April 28, 2021. Version: 1.0.0

Database Credentialed Access

Phenotype Annotations for Patient Notes in the MIMIC-III Database

Edward Moseley, Leo Anthony Celi, Joy Wu, et al.

Clinical notes, annotated by at least two expert annotators for over ten patient phenotypes, including advanced cancer, substance abuse, and treatment non-adherence.

patient classification natural language processing

Published: March 5, 2020. Version: 1.20.3