Data for: An analysis of Ambulatory Blood Pressure Monitoring (ABPM).

Published: 12 November 2017| Version 1 | DOI: 10.17632/y4dh3b3tfx.1
khalida Douibi, Mohamed malik Benabid, Nesma Settouti, mohammed amine chikh


The Ambulatory Blood Pressure Monitoring (ABPM) dataset is a new multi-label database with 40 ABPM features for 270 numeric patient records categorized into one or more out of 6 labels. It is released to the public, in order to allow comparative experiments by other researchers and especially medical researchers while the publicly available multi-label medical datasets are very rare. The ABPM is the record of the Blood Pressure for a duration of 24 hours, the interpretation of such data gives a relevant information about the general health status of the patient, for that the indication of this type of examination is increasing nowadays. Unfortunately in the literature, there are just a few theoretical works interested to analyze the generated data; this is probably due to their complexity or the difficulties of understanding their medical context or the lack of the data for the test, the proposed dataset aims to resolve this problem by making available to researchers a data annotated by an expert in the field.



Health Sciences, Data Mining, Machine Learning, Blood Pressure, Data Analysis, Ambulatory Pressure Monitoring, Cardiology, Blood Pressure Variability