Disease Progression of Hypertrophic Cardiomyopathy: Modeling Using Machine Learning.

ABSTRACT:

Background

Cardiovascular disorders in general are responsible for 30% of deaths worldwide. Among them, hypertrophic cardiomyopathy (HCM) is a genetic cardiac disease that is present in about 1 of 500 young adults and can cause sudden cardiac death (SCD).

Objective

Although the current state-of-the-art methods model the risk of SCD for patients, to the best of our knowledge, no methods are available for modeling the patient's clinical status up to 10 years ahead. In this paper, we propose a novel machine learning (ML)-based tool for predicting disease progression for patients diagnosed with HCM in terms of adverse remodeling of the heart during a 10-year period.

Methods

The method consisted of 6 predictive regression models that independently predict future values of

SUBMITTER: Piculin M 

PROVIDER: S-EPMC8851344 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature