This comprehensive review explores the pivotal role of ensemble machine learning
techniques in Quantitative Structure-Activity Relationship (QSAR) modeling for drug …

This study explores the use of Quantitative Structure-Activity Relationship (QSAR) studies
using genetic algorithm (GA) and LightGBM to search for acetylcholinesterase (AChE) …

Accurate prediction of blood glucose levels is essential for type 1 diabetes optimizing insulin
therapy and minimizing complications in patients with type 1 diabetes. Using ensemble …

Near-real time estimation of damage to buildings and infrastructure, referred to as damage
nowcasting in this study, is crucial for empowering emergency responders to make informed …

Understanding the spatial and temporal patterns of forest fires, along with the key factors
influencing their occurrence, and accurately forecasting these events are crucial for effective …

One of the leading causes of mortality worldwide is cardiovascular disease (CVD).
Electrocardiography (ECG) is a noninvasive and cost-effective tool to diagnose the heart's …

Heart failure disease is a complex clinical issue which has more impact on life of human
begins. Hospitals and cardiac centers frequently employ electrocardiogram (ECG) tool to …

Determining the classification of motor competence is an essential aspect of physical activity
that must be carried out during school years. The objective is to evaluate motor competence …

Coronary Artery Disease (CAD) is an increasingly prevalent disorder that significantly affects
both longevity and quality of life, particularly among people aged 30 to 60. Lifestyle …

Coronary Artery Disease (CAD) imposes a significant global health burden, profoundly
impacting morbidity and mortality rates worldwide. Accurate prediction of CAD is paramount …