Resources

Reliable longitudinal risk prediction for hospitalized patients is needed to provide quality care. Our goal is to foster the development of generalizable models capable of leveraging clinical notes to predict healthcare-associated diseases 24–96 hou…

The surface electrohysterogram (EHG) has emerged as a promising diagnostic tool for non-invasive automated preterm birth prediction. The existing automated preterm birth prediction methods rely on the use of uterine EHG records coming from spontaneo…

GOSSIS-1 is a modern, free, open-source in-hospital mortality prediction algorithm for critical care patients, achieving excellent discrimination and calibration across three countries (Australia, New Zealand and the USA). GOSSIS-1 was developed on …

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…

Extended hospital stays and readmissions are associated with high costs and burden of disease. Effective ways to predict patient outcomes, select those at risk of adverse outcomes, and to prevent these accordingly, are lacking. Physical activity mea…

The National Health and Nutrition Examination Survey (NHANES) is a nationally representative study that collects demographic, socioeconomic, dietary, and health-related information from 10,000 Americans annually. In Wave G (2011-2012) and Wave H (20…

The development of robust echocardiography analyses has been limited by the scarcity of well-annotated, labeled echocardiogram datasets. We introduce the Structured Viewing Classification Annotations From the MIMIC-IV-ECHO Dataset (ECHOVIEW), a deri…

Clinical risk prediction based on machine learning algorithms plays a vital role in modern healthcare. A crucial component in developing a reliable prediction model is a high-quality dataset with time series clinical events. In this work, we release…

Individuals who menstruate are frequently led to believe that there is a standard menstrual cycle, typically characterized as 28 days in length with predictable and uniform patterns. This framing often emphasizes cycle dates as the only relevant met…

This dataset is a curated subset of MIMIC-III (v1.4), specifically formatted to facilitate reproducibility of the experiments in the work t-PatchGNN. It serves as part of a benchmark designed for forecasting irregular multivariate clinical time seri…