Resources

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 …

The applicability of current lesion segmentation models for chest X-rays (CXRs) has been limited both by a small number of target labels and the reliance on complex, expert-level text inputs, creating a barrier to practical use. To address these lim…

MIMIC-IV-Ext-CLIF is a derived dataset of MIMIC-IV v3.1, transformed into the Common Longitudinal ICU data Format (CLIF). CLIF is an open-source critical care data model developed by a consortium of more than 10 US academic medical centers to standa…

Pulmonary embolism (PE) is a leading cause of preventable in-hospital mortality. Advances in diagnosis, risk stratification, and prevention can improve outcomes. Large, publicly available datasets are needed to move research forward but are lacking …

This dataset contains airway gauge pressure, inspiratory differential pressure, and pulse oximetry waveforms collected from 20 healthy adult participants (10 females, 10 males) during simulated obstructive sleep apnoea (OSA) trials. Recordings inclu…

This dataset provides multimodal neurophysiological and physiological recordings collected to investigate stress resilience. It comprises electroencephalography, functional near-infrared spectroscopy, electrodermal activity, blood volume pulse, inte…

This repository releases the EchoGraph-annotated ECHO-NOTE2NUM dataset, containing 45,794 echocardiography reports with comprehensive entity and relation annotations. Each report from the ECHO-NOTE2NUM dataset has been automatically annotated using …

InReDD-Dataset-PAN924 is a collection of 924 radiographic images annotated with mouth and teeth labels by specialists from the InReDD research group. InReDD (Interdisciplinary Research Group in Digital Dentistry) is a collaborative research initiati…

MedVAL-Bench is a dataset containing physician evaluations of errors in language model (LM)-generated medical text. The dataset spans 6 diverse medical text generation tasks and includes annotations from 12 physicians on clinically significant error…

Doctor-patient consultations require multi-turn, context-aware communication tailored to diverse patient personas. Training or evaluating doctor LLMs in such settings requires realistic patient interaction systems. However, existing simulators often…