This article presents a systematic mapping study dedicated to conduct a literature review on
machine learning and IoT applied in the identification of diseases through heart sounds …

Given the world-wide prevalence of heart disease, the robust and automatic detection of
abnormal heart sounds could have profound effects on patient care and outcomes. In this …

Cardiac auscultation is one of the most conventional approaches for the initial assessment
of heart disease, however the technique is highly user-dependent and with low repeatability …

Abnormal heart sounds may have diverse frequency characteristics depending upon
underlying pathological conditions. Designing a binary classifier for predicting normal and …

In this paper we propose a feature extraction algorithm for classifying Coronary Artery
Disease (CAD) patients from Photoplethysmogram (PPG) signals. Several domain …

In this paper we propose a novel process flow of a low-cost, non-invasive screening system
for identifying Coronary Artery Disease (CAD) patients using a two-stage classification …

Feature subset selection and identification of appropriate classification method plays an
important role to optimize the predictive performance of supervised machine learning …

Coronary Artery Disease (CAD) is a leading cause of death globally. Coronary angiography,
the clinical diagnosis for CAD involves a surgery and admission to hospital. While this is a …

This article presents a systematic mapping study dedicated to conduct a literature review on
machine learning and IoT applied in the identification of diseases through heart sounds …

Deep Learning (DL) has proved to be a promising methodology for classification,
recognition, prediction and end-to-end tasks. Recently it has proved its high potential in …