Resources


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, Yeasul Kim, Momsen Reincke, Lichy Han, Ben Deverett, Mohammad Amin Sadeghi, Abdel badih El Ariss, Marc Ghanem, David Seong, Andrew Lee, Caitlin Coombes, Brad Bradshaw, Mahir Sufian, Hyo Jung Hong, Teresa Nguyen, Mohammad Rasouli, Komal Kamra, Mark Burbridge, James McAvoy, Roya Saffary, Stephen Parnell Ma, Dev Dash, James Xie, Ellen Wang, Cliff Schmiesing, Nigam Shah, Nima Aghaeepour

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.

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

Published: April 9, 2025. Version: 1.0.0

Database Restricted Access

Swiss-Mammo: A physician-written, synthetic dataset of German mammography reports

Daniel Reichenpfader, Sandro von Däniken, Harald Marcel Bonel

Swiss-Mammo: A physician-written, synthetic dataset of 28 German mammography reports. The dataset is stratified based on BI-RADS categories and available in German and English.

radiology mammography structured reporting bi-rads

Published: June 24, 2025. Version: 1.0.1

Database Credentialed Access

MIMIC-IV-Ext-BHC: Labeled Clinical Notes Dataset for Hospital Course Summarization

Asad Aali, Dave Van Veen, Yamin Arefeen, Jason Hom, Christian Bluethgen, Eduardo Pontes Reis, Sergios Gatidis, Namuun Clifford, Joseph Daws, Arash Tehrani, Jangwon Kim, Akshay Chaudhari

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.

natural language processing clinical notes brief hospital course text summarization machine learning

Published: Feb. 3, 2025. Version: 1.2.0

Database Credentialed Access

MIMIC-IV-Ext-BHC: Labeled Clinical Notes Dataset for Hospital Course Summarization

Asad Aali, Dave Van Veen, Yamin Arefeen, Jason Hom, Christian Bluethgen, Eduardo Pontes Reis, Sergios Gatidis, Namuun Clifford, Joseph Daws, Arash Tehrani, Jangwon Kim, Akshay Chaudhari

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.

natural language processing clinical notes brief hospital course text summarization machine learning

Published: Feb. 3, 2025. Version: 1.2.0

Challenge Open Access

2018 IEEE BHI and BSN Data Challenge

Tom Pollard, Alistair Johnson, Jesse Raffa

A challenge to explore real clinical questions in critically ill patients using the MIMIC. A collaboration with the IEEE Conference on Biomedical and Health Informatics 2018 and the IEEE Conference on Body Sensor Networks.

weekend effect ieee challenge mimic

Published: Feb. 5, 2018. Version: 1.0

Model Credentialed Access

What's in a Note? Unpacking Predictive Value in Clinical Note Representations

Tristan Naumann, William Boag

Word vectors corresponding to the AMIA 2018 Informatics Summit paper of the same name.

Published: Jan. 7, 2018. Version: 0.1

Database Credentialed Access

National Institutes of Health Stroke Scale (NIHSS) Annotations for the MIMIC-III Database

Jiayang Wang, Xiaoshuo Huang, Lin Yang, Jiao Li

A dataset of annotated NIHSS scale items and corresponding scores from stroke patients discharge summaries in MIMIC-III.

Published: Jan. 25, 2021. Version: 1.0.0

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, Yeasul Kim, Momsen Reincke, Lichy Han, Ben Deverett, Mohammad Amin Sadeghi, Abdel badih El Ariss, Marc Ghanem, David Seong, Andrew Lee, Caitlin Coombes, Brad Bradshaw, Mahir Sufian, Hyo Jung Hong, Teresa Nguyen, Mohammad Rasouli, Komal Kamra, Mark Burbridge, James McAvoy, Roya Saffary, Stephen Parnell Ma, Dev Dash, James Xie, Ellen Wang, Cliff Schmiesing, Nigam Shah, Nima Aghaeepour

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.

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

Published: April 9, 2025. Version: 1.0.0