Resources


Model Credentialed Access

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

Eric Lehman, Sarthak Jain, Karl Pichotta, Yoav Goldberg, Byron Wallace

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

AMR-UTI: Antimicrobial Resistance in Urinary Tract Infections

Michael Oberst, Soorajnath Boominathan, Helen Zhou, Sanjat Kanjilal, David Sontag

AMR-UTI is a freely accessible dataset, derived from electronic health record (EHR) information on over 100,000 urinary tract infections (UTI) treated at Massachusetts General Hospital and Brigham & Women's Hospital in Boston, MA, USA.

antibiotic resistance causal inference policy learning antimicrobial resistance urinary tract infection clinical decision support machine learning

Published: Nov. 4, 2020. Version: 1.0.0


Database Credentialed Access

MIMIC-III - SequenceExamples for TensorFlow modeling

Jonas Kemp, Kun Zhang, Andrew Dai

MIMIC-III data converted into TensorFlow SequenceExample format, for use in modeling pipelines.

tensorflow sequence modeling machine learning deep learning

Published: Sept. 29, 2020. Version: 1.0.0


Database Credentialed Access

Phenotype Annotations for Patient Notes in the MIMIC-III Database

Edward Moseley, Leo Anthony Celi, Joy Wu, Franck Dernoncourt

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: 1.20.03


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 Open Access

Clinical data from the MIMIC-II database for a case study on indwelling arterial catheters

Jesse Raffa

Dataset extracted from MIMIC-II for a tutorial on effectiveness of indwelling arterial catheters in hemodynamically stable patients with respiratory failure for mortality outcomes.

Published: Oct. 28, 2016. Version: 1.0


Database Credentialed Access

MIMIC-Ext-MIMIC-CXR-VQA: A Complex, Diverse, And Large-Scale Visual Question Answering Dataset for Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, Jungwoo Oh, Lei JI, Eric Chang, Tackeun Kim, Edward Choi

We introduce MIMIC-Ext-MIMIC-CXR-VQA, a complex, diverse, and large-scale dataset designed for Visual Question Answering (VQA) tasks within the medical domain, focusing primarily on chest radiographs.

question answering machine learning evaluation chest x-ray radiology benchmark electronic health records multimodal deep learning visual question answering

Published: July 19, 2024. Version: 1.0.0


Database Credentialed Access

MIMIC-IV-ED

Alistair Johnson, Lucas Bulgarelli, Tom Pollard, Leo Anthony Celi, Roger Mark, Steven Horng

A large database of emergency department admissions.

emergency department ed emergency mimic-iv electronic health record mimic

Published: Jan. 5, 2023. Version: 2.2


Database Credentialed Access

MIMIC-IV-Note: Deidentified free-text clinical notes

Alistair Johnson, Tom Pollard, Steven Horng, Leo Anthony Celi, Roger Mark

Deidentified free-text clinical notes for patients in the MIMIC-IV Clinical Database.

deidentification critical care electronic health record natural language processing clinical notes mimic

Published: Jan. 6, 2023. Version: 2.2


Database Credentialed Access

Predictors of Hospital Onset Infection: A Matched Retrospective Cohort Dataset

Ziming Wei, Luke Sagers, Caroline McKenna, Ted Pak, Chanu Rhee, Michael Klompas, Sanjat Kanjilal

NPA-CP is a freely accessible dataset derived from electronic health record (EHR) information at MGB between 2015 and 2024. The dataset includes 11 different pathogens and can be used to predict hospital-onset infections for these pathogens.

electronic health records infection control clinical machine learning infectious diseases hospital onset infection colonization pressure

Published: Nov. 4, 2025. Version: 1.0.0