Abstract Nowadays, Artificial Intelligence (AI) and machine learning (ML) have successfully
provided automated solutions to numerous real-world problems. Healthcare is one of the …

Being an essential component in the plastics industry, phthalates are ubiquitous in the
environment and in everyday life. They are considered environmental contaminants that …

Automatic screening approaches can help diagnose Cardiovascular Disease (CVD) early,
which is the leading source of mortality worldwide. Electrocardiogram (ECG/EKG)-based …

The identification and prognosis of the potential for developing Cardiovascular Diseases
(CVD) in healthy individuals is a vital aspect of disease management. Accessing the …

In general, cardiac arrest results in an inability to pump enough blood for the body's needs.
Through this, the organs and tissues get enough oxygen and nutrients for their metabolic …

This study aims to use a machine learning (ML)-based enhanced diagnosis and survival
model to predict heart disease and survival in heart failure by combining the cuckoo search …

A significant proportion of patients experience delays in the diagnosis of heart failure due to
the non‐specific signs and symptoms of the syndrome. Diagnostic tools such as …

A visual analysis may accurately predict cardiac arrest, making it a potent educational tool
for raising public awareness of health issues. By predicting cardiac arrest earlier …

Heart disease remains the major cause of death, despite recent improvements in prediction
and prevention. Risk factor identification is the main step in diagnosing and preventing heart …

Heart disease (HD) is one of the leading causes of death in humans, posing a heavy burden
on society, families, and patients. Real-time prediction of HD can reduce mortality rates and …