Cardiovascular diseases, including heart disease, pose a significant global health
challenge, contributing to a substantial burden on healthcare systems and individuals. Early …

Advancements in technology and computational power have significantly diversified the field
of medical sciences, especially in diagnosing human cardiac disorders, which is currently …

E-Healthcare has emerged as a pivotal domain in transforming traditional healthcare
systems, leveraging technology to enhance efficiency and precision. This paper focuses on …

Introduction Identifying people at risk of cardiovascular diseases (CVD) is a cornerstone of
preventive cardiology. We developed machine learning (ML) algorithms and investigated …

Cardiovascular diseases (CVDs) are common diseases that impact the heart or vascular
system. Since early discovery significantly improves survival chances, precise prediction …

Abstract Machine learning algorithms have been used in diverse areas among applications,
including healthcare. However, to fit an effective and optimal machine learning model, the …

Predicting the first signs of heart disease is essential for timely diagnosis and treatment, as
this condition is a significant cause of death globally. Knowing in advance who is at risk for …

With the increase in mortality rate around the world in recent years, cardiovascular diseases
(CVD) have swiftly become a leading cause of morbidity, and therefore there arises a need …

In this paper we propose a novel decision support framework based on deep learning for
cardiovascular disease prediction. The proposed framework based on an innovative stacked …

Cardiovascular disease is one of the main reasons for demise of people in the world today,
whether it is a developed country or a developing country. It is not only affecting the people …