Resources

The Contextualized Race and Ethnicity Annotations for Clinical Text (C-REACT) dataset is a large publicly available corpus of sentences from clinical notes manually annotated for information related to race and ethnicity (RE). The corpus presented h…

Transformer-based neural language models have led to breakthroughs for a variety of natural language processing (NLP) tasks. However, most models are pretrained on general domain data. We propose a methodology to produce a model focused on the clini…

MIMIC-II documents a diverse and large population of intensive care unit patient stays and contains comprehensive and detailed clinical data, including physiological waveforms and minute-by-minute trends for a subset of records. It establishes a uni…

Patient’s unique information needs about their hospitalization can be addressed using clinical evidence from electronic health records (EHRs) and artificial intelligence (AI). However, robust datasets to assess the factuality and relevance of AI-gen…

This resource comprises three clinical time series datasets used in the paper Trajectory Flow Matching with Applications to Clinical Time Series Modeling to evaluate models for handling irregularly sampled data in critical care settings. The ICU Sep…

Emergency department (ED) patients often present with undiagnosed complaints, and can exhibit rapidly evolving physiology. Therefore, data from continuous physiologic monitoring, in addition to the electronic health record, is essential to understan…

Interoperability of healthcare data has become increasingly important given the increase in deployment of data driven algorithms in clinical settings. The Fast Healthcare Interoperability Resources (FHIR) standard has emerged as a promising mechanis…

Discharge summaries in Electronic Health Records (EHRs) are crucial for clinical decision-making, but their length and complexity make information extraction challenging, especially when dealing with accumulated summaries across multiple patient adm…

Sharing patient data such as clinical notes among clinicians and researchers is fundamental to advancements in clinical practice and biomedical research. Prior to distribution, it is often necessary and legally mandated to remove identifiers such as…

Unlocking the full potential of clinical notes within electronic health records presents a challenge for large scale, computational analyses. Many studies that incorporate information from clinical notes do so with simple word-matching approaches an…