Resources

Existing chest radiograph datasets, such as CheXpert and ChestX-ray14, have driven the development of new machine learning approaches to achieve expert or near-expert level performance on a variety of tasks. The primary focus of models developed usi…

Continuous monitoring of arterial blood pressure (BP) in non-clinical (ambulatory) settings is essential for a proper understanding of numerous health conditions. While conventional ambulatory BP devices exist, they are uncomfortable, bulky, and in…

The SICdb dataset offers insights into over 27 thousand intensive care admissions, including therapies and data on preceding surgeries. Data were collected between 2013 and 2021 from four different intensive care units at the University Hospital Sal…

COVID Data for Shared Learning (CDSL) is a multimodal database comprising de-identified medical data from 4,479 patients who were hospitalized with confirmed or suspected COVID-19 in the Spanish 'HM Hospitales' group from 2019-12-26 to 2021-02-13. T…

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 …

Medical Information Mart for Intensive Care Brazil (MIMIC-BR) is a database of anonymized clinical data from ICU and hospital admissions in Brazil. The dataset format and intended use match the original large, freely available database comprising de…

This repository contains a de-identified and curated patient-level dataset for modeling the impact of fine-grained environmental and patient-level factors on nosocomial acquisition of a wide range of drug-susceptible and drug-resistant pathogens. Th…

Emergency department (ED) overcrowding leads to delayed care, increased patient risk, and inefficient resource use. The MIMIC-IV-Ext Triage Instruction Corpus (MIETIC) addresses this by providing 9,629 structured triage cases from MIMIC-IV, aligned …

Named Entity Recognition (NER) and Entity Normalization (EN) are fundamental tasks in information extraction, particularly in the biomedical and clinical domains. NER identifies textual mentions of entities, while EN maps these mentions to unique id…

The number of publicly available ECG datasets has increased tremendously in the past few years and several of these datasets have developed into widely used benchmarking datasets. However, most of them exhibit a common limitation, namely the relianc…