Problem of choosing methods has been presented for increasing the reliability of solutions
while reducing the time resource for researching the state space of a particular object …

Heart disease is one of the most widely spreading and deadliest diseases across the world.
In this study, we have proposed hybrid model for heart disease prediction by employing …

Feature selection improves the classification performance of machine learning models. It
also identifies the important features and eliminates those with little significance …

The earlier prediction of heart diseases and appropriate treatment are important for
preventing cardiac failure complications and reducing the mortality rate. The traditional …

Cardiovascular diseases (CVDs) pose a significant global public health challenge,
necessitating precise risk assessment for proactive treatment and optimal utilization of …

Because of the scarcity of caregivers and the high cost of medical devices, it is difficult to
keep track of the aging population and provide assistance. To avoid deterioration of health …

Heart disease is one of the major cause of mortality in the world today. Prediction of
cardiovascular disease is a critical challenge in the field of clinical data analysis. With the …

One of the leading causes of death is heart disease. The prediction of cardiovascular
disease remains as a significant challenge in the clinical data analysis domain. Although …

Throughout the past several decades, cardiac illnesses have been the leading cause
fatalities worldwide and have become the condition that poses the greatest threat to survival …

This study investigates the worldwide predicament presented by cardiovascular diseases
(CVDs), which are the primary contributor to mortality, accounting for around 17.9 million …