Due to their widespread prevalence and impact on quality of life, cardiovascular diseases
(CVD) pose a considerable global health burden. Early detection and intervention can …

In today's world, services are improved and advanced in every field of life. Especially in the
health sector, information technology (IT) plays a vigorous role in electronic health (e …

Classroom EEG recordings classification has the capacity to significantly enhance
comprehension and learning by revealing complex neural patterns linked to various …

Alcohol use disorder (AUD) is a common mental illness with high morbidity and disability.
The discovery of laboratory biomarkers has progressed slowly, resulting in suboptimal …

This study proposes a two-stage methodology for predicting wind energy production using
time, environmental, technical, and locational variables. In the first stage, machine learning …

Objective This study aims to identify potential lipid biomarkers and metabolic pathways
associated with oral cancer (OC). Then to establish and evaluate disease classification …

Cardiovascular diseases are one of major causes for death globally. Prediction of these
diseases becomes a bit complex in the fields like clinical analysis. It is observed that over …

Recently, thyroid disease has been a leading cause of mortality, underscoring the
importance of early diagnosis to mitigate its impact. Researchers have randomly employed …

Background/Objectives: The research addresses algorithmic bias in deep learning models
for cardiovascular risk prediction, focusing on fairness across demographic and …

Prediction of Cardiovascular disease (CVD) with a more accurate and timely diagnosis is
crucial to ensure accurate classification, which assists medical professionals in providing …