Resources

MIMIC-III is a large, freely-available database comprising deidentified health-related data associated with over 40,000 patients who stayed in critical care units of the Beth Israel Deaconess Medical Center between 2001 and 2012 [1]. The MIMIC-III C…

This dataset provides clinical Named Entity Recognition (NER) and Assertion Classification (AC) annotations for 400 discharge summaries from MIMIC-IV-Note (v2.2), designed to support research on computer-assisted ICD coding and related clinical natu…

The MIMIC-IV-Echo module contains structured echocardiographic measurements and DICOM files from echocardiography exams. Structured measurements are available from 206,488 echocardiogram studies (including 179,928 transthoracic, 16,389 stress, and 1…

This dataset was designed and created to enable advancements in healthcare-focused large language models, particularly in the context of retrieval-augmented clinical question-answering capabilities. Developed using a self-constructed pipeline based …

This challenge, sponsored by SNOMED International, seeks to advance the development of Entity Linking models that operate on unstructured clinical texts. Participants in the challenge will train entity linking models using a subset of MIMIC-IV-Note …

MIMIC-III is a large, freely-available database comprising deidentified health-related data associated with over forty thousand patients who stayed in critical care units of the Beth Israel Deaconess Medical Center between 2001 and 2012. The databas…

Applying methods in natural language processing on electronic health records (EHR) data is a growing field. Existing corpus and annotation focus on modelling textual features and relation prediction [1] . However, there is a paucity of annotated cor…

Available here is a gold standard corpus of 2,434 nursing notes that have been thoroughly deidentified by a multi-pass process that included meticulous reviews by three or more experts working independently, as well as by a variety of automated meth…

Widespread disparities in clinical outcomes exist between different demographic groups in the United States. A new line of work in medical sociology has demonstrated physicians often use stigmatizing language in electronic medical records within cer…

Opioid use disorder (OUD) is underdiagnosed in health system settings, limiting research on OUD using electronic health records (EHRs). Medical encounter notes can enrich structured EHR data with documented signs and symptoms of OUD and social risks…