Detection of subclinical rheumatic heart disease in children using a deep learning algorithm on digital stethoscope: a study protocol.

ABSTRACT:

Introduction

Rheumatic heart diseases (RHDs) contribute significant morbidity and mortality globally. To reduce the burden of RHD, timely initiation of secondary prophylaxis is important. The objectives of this study are to determine the frequency of subclinical RHD and to train a deep learning (DL) algorithm using waveform data from the digital auscultatory stethoscope (DAS) in predicting subclinical RHD.

Methods and analysis

We aim to recruit 1700 children from a group of schools serving the underprivileged over a 12-month period in Karachi (Pakistan). All consenting students within the age of 5-15 years with no underlying congenital heart disease will be eligible for the study. We will gather information regarding sociodemographics, anthropometric data, history of symptom

SUBMITTER: Ali F 

PROVIDER: S-EPMC8344289 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature