In the medical domain, early identification of cardiovascular issues poses a significant
challenge. This study enhances heart disease prediction accuracy using machine learning …

Heart disease remains the leading cause of death, such that nearly one-third of all deaths
worldwide are estimated to be caused by heart-related conditions. Advancing applications of …

Cardiovascular disease is the leading cause of global mortality and responsible for millions
of deaths annually. The mortality rate and overall consequences of cardiac disease can be …

Coronary heart disease is one of the major causes of deaths around the globe. Predicating a
heart disease is one of the most challenging tasks in the field of clinical data analysis …

Cardiovascular disease is a widespread and potentially fatal condition that requires
proactive preventive measures and efficient screening approaches on a global scale. To …

Detecting cardiovascular irregularities in a timely manner is crucial for preventing any fatal
risks. This research aims to devise an efficient forecasting algorithm for the timely prognosis …

In recent times, coronary artery disease (CAD) has become one of the leading causes of
morbidity and mortality across the globe. Diagnosing the presence and severity of CAD in …

Background Different machine learning techniques have been proposed to classify a wide
range of biological/clinical data. Given the practicability of these approaches accordingly …

This work presents a variety of voting ensemble models to measure human heart disease.
This work aims to give confidence to doctors to diagnose heart disease accurately. S o that …

Cardiovascular diseases (CVDs) continue to be a prominent cause of global mortality,
necessitating the development of effective risk prediction models to combat the rise in heart …