This study compares three deep learning algorithms for cardiovascular disease risk
prediction. While RBFN boasts the highest accuracy (84.07%), wekaDeeplearning4j excels …

This study compares three deep learning algorithms for cardiovascular disease risk
prediction. While RBFN boasts the highest accuracy (84.07%), wekaDeeplearning4j excels …

Cardiovascular disease (CVD) risk assessment and prognosis in otherwise healthy people
is an important part of disease management. Early detection and diagnosis of CVD …

Heart disease is a major cause of mortality worldwide and timely detection and intervention
being essential to enhancing patient health condition. Recently, deep learning techniques …

A leading cause of death globally is cardiovascular disease (CVD). Early CVD detection is
essential for successful treatment and complication prevention. Convolutional neural …

Developing a predictive model for detecting cardiovascular diseases (CVDs) is crucial due
to its high global fatality rate. With the advancements in artificial intelligence, the availability …

Cardiovascular disease (CVD), ahead of all other causes of death worldwide in this era.
There is an immediate need for accurate, reliable, and practically applicable ways of early …

Cardiovascular diseases (CVDs) remain a leading cause of morbidity and mortality globally.
Early and accurate prediction of CVD risk is crucial for preventive interventions and …

The World Health Organization (WHO) reports that cardiovascular illnesses are the primary
killer worldwide. Estimates for 2019 indicate that cardiovascular disease will be responsible …

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