Resources

Oral diseases affect nearly 3.5 billion people, with the majority residing in low- and middle-income countries. Due to limited healthcare resources, many individuals are unable to access proper oral healthcare services. Image-based machine learning …

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…

This dataset presents a curated collection of preprocessed and labeled clinical notes derived from the MIMIC-IV-Note database. The primary aim of this resource is to facilitate the development and training of machine learning models focused on summa…

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…

Offline reinforcement learning (RL) holds promise for improving healthcare decision-making. However, most existing approaches rely on discretising patient trajectories into strictly regular time intervals. This is done to improve compatibility with …

A recent study showed that infrared (IR) sensors may be prone to calibration discrepancies among darker-pigmented patients. Similar disparities have already been verified in pulse oximetry. This raises questions about whether thermometry measurement…

Retrospectively collected medical data has the opportunity to improve patient care through knowledge discovery and algorithm development. Broad reuse of medical data is desirable for the greatest public good, but data sharing must be done in a manne…

The CPS dataset, assembled at Klinikum Esslingen, Germany, encompasses 113 diagnostic polysomnographic sleep recordings. These recordings include up to 36 raw and 23 derived data channels, alongide 81 types of annotated events for each participant, …