In the last decade, healthcare systems have played an effective role in improving medical
services by monitoring and diagnosing patients' health remotely. These systems, either in …

In recent years, machine learning is attaining higher precision and accuracy in clinical heart
disease dataset classification. However, literature shows that the quality of heart disease …

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

Indonesia is an ASEAN country with the most motorcycle users, where onethird of its
population own motorcycles. The automatic motorcycle is the most widely used type due to …

The primary objective in building predictive analytics models is to achieve optimal accuracy
with real datasets. The limitations of existing models lie in their storage capacity, which …

Cardiovascular disease (CVD) is now one of the leading causes of death worldwide and
was also thought to be a serious illness in the mid and old ages. Artificial intelligence and …

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 …

This study aims to investigate the effectiveness of local interpretable model-agnostic
explanation (LIME) and Shapley additive explanation (SHAP) approaches for chronic heart …

The existing heart failure risk prediction models are developed based on machine learning
predictors. The objective of this study is to identify the key risk factors that affect the survival …

Recent healthcare reports indicate clearly an increasing mortality rates worldwide which
puts a significant burden on the healthcare sector due to different diseases. Coronary artery …