<?xml version='1.0' encoding='UTF-8'?><metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns="http://dublincore.org/documents/dcmi-terms/"><dcterms:title>MIMIC-BP</dcterms:title><dcterms:identifier>https://doi.org/10.7910/DVN/DBM1NF</dcterms:identifier><dcterms:creator>Samsung R&amp;D Institute Brazil, SRBR</dcterms:creator><dcterms:creator>Otávio A. B. Penatti</dcterms:creator><dcterms:creator>Carlos Caetano</dcterms:creator><dcterms:creator>Vinicius H. Cene</dcterms:creator><dcterms:creator>Ivandro Sanches</dcterms:creator><dcterms:creator>Victor V. Gomes</dcterms:creator><dcterms:creator>Lizeth S. B. Cabrera</dcterms:creator><dcterms:creator>Thomas Beltrame</dcterms:creator><dcterms:creator>Wonkyu Lee</dcterms:creator><dcterms:creator>Sanghyun Baek</dcterms:creator><dcterms:publisher>Harvard Dataverse</dcterms:publisher><dcterms:issued>2023-11-15</dcterms:issued><dcterms:modified>2024-11-21T16:41:45Z</dcterms:modified><dcterms:description>We propose a derivative dataset (derived from MIMIC-III Waveform Database Matched Subset) composed of 380 hours of the most common biomedical signals, including arterial blood pressure, photoplethysmograph, and electrocardiogram for 1,524 de-identified subjects, each having 30 segments of 30 seconds of those signals. For more detailed information, please refer to the scientific article at this link:
&lt;a href="https://www.nature.com/articles/s41597-024-04041-1">https://www.nature.com/articles/s41597-024-04041-1&lt;/a></dcterms:description><dcterms:subject>Computer and Information Science</dcterms:subject><dcterms:date>2023-11-15</dcterms:date><dcterms:contributor>Samsung R&amp;D Institute Brazil, SRBR</dcterms:contributor><dcterms:dateSubmitted>2023-11-15</dcterms:dateSubmitted><dcterms:license>ODbL 1.0</dcterms:license></metadata>