Resources


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, Brihat Sharma, Matthew Churpek, Dmitriy Dligach, Majid Afshar

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.

machine learning question generation question answering

Published: July 28, 2022. Version: 1.0

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-IV-ED

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

A large database of emergency department admissions.

mimic emergency department ed emergency mimic-iv electronic health record

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 mimic critical care natural language processing clinical notes electronic health record

Published: Jan. 6, 2023. Version: 2.2