Resources

A retrospective dataset of continuous vital sign time-series recorded from dogs and cats during general anesthesia, collected from a veterinary hospital's anesthesia machines and patient monitors.

This project utilizes data derived from the MIMIC-III, MIMIC-IV, eICU-CRD, SICdb and ZhejiangProvinceICUdb databases. The ethics approval of this dataset follows from that of these source datasets. Furthermore, all authors have obtained the necessary

CARMEN-I is a Spanish corpus of 2,000 clinical records from Hospital Clínic, Barcelona. It covers COVID-19 patients and comorbidities, serving as a resource for training clinical NLP models and researchers in NLP applied to clinical documents.

A curated dataset of paired radiology reports derived from MIMIC-CXR, with controlled clinical rewrites and expert annotations. Designed for meta-evaluation of report evaluation metrics, focusing on clinical significance, error types, and severity.

488 MIMIC-IV cases contain initial vignettes, discharge summaries, test names and diagnoses; 71 test cases are clinician-reviewed. Designed primarily for SDBench, they also support diagnostic benchmarks and clinical information extraction.

This database comprises clinical, transcranial Doppler (TCD), and vital signs monitoring data from adult patients with neurocritical conditions in a neurointensive care unit.

MNE contains clinical information from 300k MIMIC-IV-Note discharge summaries, converted into structured tabular data. All sections of the discharge summaries are covered, including patient history, allergies, medications, pertinent findings, etc.

EHRNote-ChatQA is a benchmark of 967 patient-level multi-turn QA samples over longitudinal MIMIC-IV discharge summaries, with 16,072 medical-expert-verified content questions and evidence-grounding questions.

Note-level stigmatizing language and misgendering annotations for 754 MIMIC-IV-Note discharge summaries, with linked demographic variables and no clinical note text.

De-identified hospital encounter-level data from a cluster-randomized trial testing a nursing-surveillance-based early warning system across 74 hospital units, including outcomes for mortality, length of stay, sepsis, and ICU transfer.