Home // HEALTHINFO 2023, The Eighth International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing // View article
Authors:
Carlos Barroso-Moreno
Hector Espinos Morato
Enrique Puertas
Juan Jose Beunza Nuin
José Vicente Monmeneu
David Moratal
María P. López-Lereu
Keywords: Machine Learning; right ventricular involve- ment; Pulmonary Vascular Resistance; Cardiomyopathy.
Abstract:
Cardiomyopathy is a disease of the heart muscle that makes it harder for the heart to pump blood. Previous studies have focused on the left ventricle, but in recent years the relevance of the right ventricle has been the focus of current research. The aim is to determine those clinical and cardiac parameters that influence right ventricular involvement in is- chaemic and non-ischaemic cardiomyopathy. The used database is composed of 56,447 subjects collected from 2008 to 2020 by ASCIRES Biomedical Group. The methodology is divided into two blocks: in the clinical aspect, decision trees are used to gain interpretability and in the technical aspect, Machine Learning (ML) is used for a greater degree of prediction. The results show the influence of the difference in aortic artery beat volume and vascular pulmonary volume as key factors, reaching an Area Under the Curve (AUC) of 92.3% using RapidMiner tool with decision trees algorithm. The conclusions demonstrate the ability to identify clinical variables of right ventricular involvement and consequently reduce the number of diagnostic tests and associated times in a situation of cardiomyopathy.
Pages: 1 to 8
Copyright: Copyright (c) IARIA, 2023
Publication date: November 13, 2023
Published in: conference
ISSN: 2519-8491
ISBN: 978-1-68558-105-3
Location: Valencia, Spain
Dates: from November 13, 2023 to November 17, 2023