Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

Although a posteriori dietary patterns (DPs) naturally reflect actual dietary behavior in a
population, their specificity limits generalizability. Among other issues, the absence of a …

Nowadays, modern technology is widespread in sports; therefore, finding an excellent
approach to extracting knowledge from data is necessary. Machine Learning (ML) …

In an era characterized by unprecedented virtual connectivity, paradoxically, individuals
often find themselves disconnected from genuine human interactions. The advent of remote …

We aimed to analyze the relationship between coffee, tea, and carbonated beverages and
cardiovascular risk factors. We used data from the fourth to eighth Korea National Health …

Background: Numerous factors, including metformin doses and treatment adherence, may
contribute to significant variations in glycemic control and adiposity markers of type 2 …

Diabetes is an important global health concern. According to the World Health Organization,
the Kingdom of Saudi Arabia (KSA) has 2.8 to 4.3 million diabetic patients between the ages …

Purpose The previous studies that examined the effectiveness of unsupervised machine
learning methods versus traditional methods in assessing dietary patterns and their …

Machine Learning could help the healthcare industry manage huge amounts of data and
discover hidden trends and patterns that could help us better understand disease …

Cardiovascular disease (CVD) is a general term referring to several heart or blood vessels
abnormality. Heart failure (HF), directly associated to (CVD), is a significant global health …