ePrints

Subtypes and Mechanisms of Hypertrophic Cardiomyopathy Proposed by Machine Learning Algorithms

Lookup NU author(s): Professor Djordje JakovljevicORCiD

Downloads

• Published version [.pdf]

Licence

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

© 2022 by the authors.Hypertrophic cardiomyopathy (HCM) is a relatively common inherited cardiac disease that results in left ventricular hypertrophy. Machine learning uses algorithms to study patterns in data and develop models able to make predictions. The aim of this study is to identify HCM subtypes and examine the mechanisms of HCM using machine learning algorithms. Clinical and laboratory findings of 143 adult patients with a confirmed diagnosis of nonobstructive HCM are analyzed; HCM subtypes are determined by clustering, while the presence of different HCM features is predicted in classification machine learning tasks. Four clusters are determined as the optimal number of clusters for this dataset. Models that can predict the presence of particular HCM features from other genotypic and phenotypic information are generated, and subsets of features sufficient to predict the presence of other features of HCM are determined. This research proposes four subtypes of HCM assessed by machine learning algorithms and based on the overall phenotypic expression of the participants of the study. The identified subsets of features sufficient to determine the presence of particular HCM aspects could provide deeper insights into the mechanisms of HCM.

Publication metadata

Author(s): Glavaski M, Preveden A, Jakovljevic D, Filipovic N, Velicki L

Publication type: Article

Publication status: Published

Journal: Life

Year: 2022

Volume: 12

Issue: 10

Online publication date: 09/10/2022

Acceptance date: 30/09/2022

Date deposited: 23/06/2023

ISSN (electronic): 2075-1729

Publisher: MDPI

URL: https://doi.org/10.3390/life12101566

DOI: 10.3390/life12101566

Altmetrics

Share