Resources


Database Credentialed Access

MIMIC-III and eICU-CRD: Feature Representation by FIDDLE Preprocessing

Shengpu Tang, Parmida Davarmanesh, Yanmeng Song, Danai Koutra, Michael Sjoding, Jenna Wiens

Features and labels from MIMIC-III and eICU-CRD produced by FIDDLE, an EHR preprocessing pipeline.

preprocessing electronic health record machine learning

Published: April 28, 2021. Version: 1.0.0


Database Open Access

MIMIC-III Clinical Database Demo

Alistair Johnson, Tom Pollard, Roger Mark

An open source demo of the MIMIC-III Clinical Database

critical care electronic health records mimic

Published: April 24, 2019. Version: 1.4


Database Open Access

MIMIC-IV demo data in the Medical Event Data Standard (MEDS)

Robin Philippus van de Water, Ethan Steinberg, Michael Wornow, Patrick Rockenschaub, Matthew McDermott

MIMIC-IV Clinical Database Demo in MEDS (Medical Event Data Standard) format.

ehr critical care electronic health record machine learning mimic meds medical event data standard

Published: Sept. 29, 2025. Version: 0.0.1


Database Credentialed Access

Multimodal Clinical Monitoring in the Emergency Department (MC-MED)

Aman Kansal, Emma Chen, Tom Jin, Pranav Rajpurkar, David Kim

A multimodal dataset of deidentified clinical and physiological data from emergency department visits, supporting research on patient outcomes, care processes, and the effects of continuous monitoring during and after the COVID-19 pandemic.

Published: Sept. 25, 2025. Version: 1.0.1


Database Credentialed Access

MIMIC-Ext-DrugDetection

Fabrice Harel-Canada, Nanyun Peng, David Goodman, Ruby Romero, Allan Nguyen, Brandon Moghanian, Anabel Salimian

This project offers a multilabel annotated dataset of clinical note sentences from MIMIC-III/IV for substance use detection. It supports NLP research for identifying various co-occurring drug use mentions in patient records.

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Published: Sept. 25, 2025. Version: 1.0.0


Database Credentialed Access

MIMIC-IV-Ext-Instr: A Dataset of 450K+ EHR-Grounded Instruction-Following Examples

Zhenbang Wu, Anant Dadu, Mike Nalls, Faraz Faghri, Jimeng Sun

This dataset contains 450K open-ended instruction-following examples generated using GPT-3.5 based on the MIMIC-IV EHR database.

large language models medical question answering instruction tuning

Published: Sept. 9, 2025. Version: 1.0.0


Database Credentialed Access

SCRIPT CarpeDiem Dataset: demographics, outcomes, and per-day clinical parameters for critically ill patients with suspected pneumonia

Nikolay Markov, Catherine A Gao, Thomas Stoeger, Mengjia Kang, Anna Pawlowski, Prasanth Nannapaneni, Luke Rasmussen, Rogan Grant, Daniel Schneider, Justin Starren, Theresa Walunas, Richard Wunderink, GR Scott Budinger, Alexander Misharin, Benjamin Singer, NU SCRIPT Study Investigators

SCRIPT seeks to delineate the host/pathogen interactions during pneumonia using multiomic analysis of bronchoalveolar lavage fluid joined with clinical data and physician adjudication.

Published: Aug. 4, 2025. Version: 1.8.0


Database Credentialed Access

MeDiSumQA: Patient-Oriented Question-Answer Generation from Discharge Letters

Amin Dada, Osman Alperen Koras, Marie Bauer, Amanda Butler, Kaleb Smith, Jens Kleesiek, Julian Friedrich

MeDiSumQA is a dataset of patient-oriented QA pairs from MIMIC-IV discharge summaries, designed to evaluate LLMs in generating safe, patient-friendly medical responses for clinical QA and healthcare communication.

Published: May 5, 2025. Version: 1.0.0


Database Restricted Access

Electrocardiogram-Capable Smartwatches: Assessing Their Clinical Accuracy and Application

Joaquin Recas, Mauro Buelga Suárez, Sergio González-Cabeza, Mario Sanz-Guerrero, Marian Diaz-Vicente, Alfonso Rebolleda, Luis Piñuel Moreno, Gonzalo Luis Alonso Salinas

This database allows the study of the feasibility of using ECG-capable smartwatches as diagnostic tools, focusing on their compliance with clinical standards and their ability to measure critical ECG parameters beyond AF detection.

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Published: April 9, 2025. Version: 1.0.0


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 machine learning brief hospital course text summarization

Published: Feb. 3, 2025. Version: 1.2.0