Machine learning methods for predicting major types of rheumatic heart diseases in children of Southern Punjab, Pakistan.

ABSTRACT:

Objective

Rheumatic heart disease (RHD) is a major health problem in the world, particularly in developing countries. This study aimed to predict mitral regurgitation (MR) and mitral stenosis (MS) RHD among children with RHD.

Methodology

Data was collected from the Pediatric Cardiology Department at Chaudhry Pervaiz Elahi Institute of Cardiology Multan, Pakistan from March to October 2019. A sample of 561 children aged 4-14 years, who were diagnosed with RHD of either MR or MS, were recruited from the hospital's outpatient department. The presence of multivariate outliers was detected, and different machine learning methods, including subset logistic regression, subset logistic regression after deletion, stepwise winsorized logistic regression, robust logistic regression, su

SUBMITTER: Shahid S 

PROVIDER: S-EPMC9596762 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature