Cardiovascular diseases present a significant global health challenge that emphasizes the
critical need for develo** accurate and more effective detection methods. Several studies …

It is yet unknown what causes cardiovascular disease (CVD), but we do know that it is
associated with a high risk of death, as well as severe morbidity and disability. There is an …

A continuous heart disease monitoring system is one of the significant applications specified
by the Internet of Things (IoT). This goal might be achieved by combining sophisticated …

One of the most difficult challenges in medicine is predicting heart disease at an early stage.
In this study, six machine learning (ML) algorithms, viz., logistic regression, K-nearest …

The health sector faces a series of problems generated by patients who miss their
scheduled appointments. The main challenge to this problem is to understand the patient's …

To identify patterns in big medical datasets and use Deep Learning and Machine Learning
(ML) to reliably diagnose Cardio Vascular Disease (CVD), researchers are currently delving …

Background Smart devices including sensors and smartphones have grown exponentially
during the past few years due to rapid growth in wireless sensor network (WSN) technology …

The use of machine learning in biomedical research has surged in recent years thanks to
advances in devices and artificial intelligence. Our aim is to expand this body of knowledge …

Introduction Application of Deep Learning (DL) methods is being increasingly appreciated
by researchers from the biomedical engineering domain in which heart sound analysis is an …

Heart sound signals play a crucial role in assessing cardiovascular health. Building upon
this, we have designed five networks to effectively classify these signals. Initially, it is …