Resources

Glaucomatous optic neuropathy (GON) is a leading cause of irreversible blindness worldwide, affecting an estimated 64.3 million people globally with projections reaching 111.8 million by 2040. Approximately 50% of cases remain undiagnosed until adva…

We present a novel dataset of 12-lead electrocardiogram (ECG) recordings developed to support the study and classification of Brugada syndrome, a rare but potentially fatal cardiac arrhythmia. The data were collected retrospectively from patients ev…

We present MIMICEchoQA, a benchmark dataset for echocardiogram-based question answering, built from the publicly available MIMIC-IV-ECHO database. Each echocardiographic study was paired with the closest discharge summary within a 7-day window, and …

We release the RadVLM instruction dataset, a large-scale resource used to train the RadVLM model on diverse radiology tasks. The dataset contains 1,115,021 image–instruction pairs spanning five task families: (i) report generation from frontal CXRs …

This original dataset contains physiological signals collected during structured acute stress induction and aerobic and anaerobic exercise sessions using a wearable device. Blood volume pulse, motion-based activity, skin temperature, and electroderm…

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 …

The CheXmask Database presents a comprehensive, uniformly annotated collection of chest radiographs, constructed from five public databases: ChestX-ray8, Chexpert, MIMIC-CXR-JPG, Padchest and VinDr-CXR. The database aggregates 657,566 anatomical seg…

Medical Visual Question Answering (VQA) is an important task in medical multi-modal Large Language Models (LLMs), aiming to answer clinically relevant questions regarding input medical images. This technique has the potential to improve the efficien…

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…

Databases that link molecular data to clinical outcomes can inform precision cancer research into novel prognostic and predictive biomarkers. However, outside of clinical trials, cancer outcomes are typically recorded only in text form within electr…