{"url":"/dataset/mimic-ii-1","name":"MIMIC II","full_name":"Multi-parameter Intelligent Monitoring for Critical Care  II database","description_markdown":"The data used in this research is a subset of the Multi-parameter Intelligent Monitoring for Critical\r\nCare (MIMIC) II database. It contains minute-by-minute time series of Heart Rate (HR), Systolic\r\nBlood Pressure (SBP), Diastolic Blood Pressure (DBP), and Mean Arterial blood Pressure (MAP)\r\narranged into records, each of which corresponds to an adult patient’s ICU stay.\r\n\r\nSource: [Vitor Cerqueira, Luis Torgo, and Carlos Soares. Early anomaly detection in time series: a hierarchical\r\napproach for predicting critical health episodes. arXiv preprint arXiv:2010.11595, 2020.] (https://github.com/vcerqueira/layered_\r\nlearning_time_series/tree/master/data_sample)","description_withheld":null,"homepage":"","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["MIMIC II"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}