Resources

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…

Symile-MIMIC is a multimodal clinical dataset derived from MIMIC-IV and MIMIC-CXR, consisting of chest X-rays (CXRs), electrocardiograms (ECGs), and blood laboratory tests. It was developed to evaluate Symile, a contrastive learning objective design…

LLaVA-Rad MIMIC-CXR features more accurate section extractions from MIMIC-CXR free-text radiology reports. Traditionally, rule-based methods were used to extract sections such as the reason for exam, findings, and impression. However, these approach…

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…

Large language models (LLMs) have recently demonstrated remarkable capabilities across a broad spectrum of tasks and applications, including the medical field. Models like GPT-4 excel in medical question answering but encounter challenges in interpr…

We release a new dataset, MS-CXR, with locally-aligned phrase grounding annotations by board-certified radiologists to facilitate the study of complex semantic modelling in biomedical vision–language processing. The MS-CXR dataset provides 1162 imag…

Measurable progress in the development of medical decision support systems has been hindered by a lack of comprehensive datasets. Many available datasets focus on narrow prediction tasks and do not include a diverse range of data types, which limits…

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…

Monitoring nociception, the flow of information associated with harmful stimuli through the nervous system even during unconsciousness, is critical for proper anesthesia care during surgery. Currently, this is done by tracking heart rate and blood p…

RadGraph2 is a dataset of 800 chest radiology reports annotated using a fine-grained entity-relationship schema, which is an expanded version of the previously introduced RadGraph dataset. In contrast with the previous approaches and the original Ra…