Resources

The PTB-XL ECG dataset is a large dataset of 21801 clinical 12-lead ECGs from 18869 patients of 10 second length. The raw signal data has been annotated by up to two cardiologists with 71 different ECG statements and is supplemented by rich metadata.

DrugEHRQA is a QA dataset containing question-answers from MIMIC-III tables and discharge summaries.

A multimodal clinical dataset consisting of CXRs, ECGs, and blood labs, designed to evaluate Symile, a simple contrastive loss that accommodates any number of modalities and allows any model to produce representations for each modality.

We present EHRXQA, the first multi-modal EHR QA dataset combining structured patient records with aligned chest X-ray images. EHRXQA contains a comprehensive set of QA pairs covering image-related, table-related, and image+table-related questions.

The Chest ImaGenome dataset is a scene graph dataset with additional chronological comparison relations for chest X-rays. It is automatically derived from the MIMIC-CXR dataset. A manually annotated gold standard is also available for 500 patients.

This is the first Brazilian Multilabel Ophthalmological Dataset with demographic information and retinal photos labeled images according to anatomical parameters, quality control, and presumed diagnosis.

A public dataset that contains information related to surgery, anesthesia, laboratory results, medications, diagnosis, and outcomes from 50% of the patients who received surgery at Seoul National University Hospital between 2011 and 2020.

This dataset presents a collection of preprocessed and labeled clinical notes derived from "MIMIC-IV-Note", and aims to facilitate the development of ML models focused on summarizing brief hospital courses (BHC) from clinical notes.

MIMIC-Diff-VQA provides a large-scale dataset for Difference visual question answering in medical chest x-ray images.

MIMIC-IV-ext-MDS-ED proposes a dataset to benchmark multimodal decision support in the emergency department. It features multimodal input (including ECG waveforms) and a comprehensive set of prediction targets (diagnoses and deterioration prediction)