Resources

Large-language models (LLMs) show promise for extracting information from clinical notes. Deploying these models at scale can be challenging due to high computational costs, regulatory constraints, and privacy concerns. To address these challenges, …

Saitama Heart Database Atrial Fibrillation (SHDB-AF) is a novel open-sourced Holter ECG database from Japan, containing data from 122 unique subjects with paroxysmal atrial fibrillation. Among the 128 recordings, 98 contain raw ECG data with rhythm …

MIMIC-CXR is a large, open source dataset that is widely-used in medical AI research. One of the limitations of this dataset is the lack of ground truth labels for the chest X-ray studies. Prior work has extracted structured labels from the MIMIC-CX…

Retrospective medical data collection is essential for advancing patient care, offering insights and supporting the development of health technology. The Medical Information Mart for Intensive Care (MIMIC)-III database has been instrumental in provi…

The development of large language models tailored for handling patients’ clinical notes is often hindered by the limited accessibility and usability of these notes due to strict privacy regulations. To address these challenges, we first create synth…

Multiple Sclerosis (MS) is an inflammatory autoimmune disease of the central nervous system, causing increased vulnerability to infections and disability among young adults. Ever since the coronavirus disease 2019 (COVID-19) outbreak, caused by seve…

The PTB-XL+ dataset is a comprehensive feature dataset that supplements the PTB-XL ECG dataset. It includes ECG features extracted via two commercial and one open-source algorithm in a harmonized format as well as median beats or, where applicable, …

This is a preprocessed dataset derived from patient records in MIMIC-III and eICU, two large-scale electronic health record (EHR) databases. It contains features and labels for 5 prediction tasks involving 3 adverse outcomes (prediction times listed…

Physiological waveforms - such as electrocardiograms (ECG), electroencephalograms (EEG), electromyograms (EMG) - are generated during the course of routine care. These signals contain information that can be used to understand underlying conditions …

WiDS (Women in Data Science) Datathon 2020: ICU Mortality Prediction focuses on patient health through data from MIT’s GOSSIS (Global Open Source Severity of Illness Score) initiative. Brought to you by the Global WiDS team, the West Big Data Innova…