Credit card fraud is a serious and growing problem. It is becoming more challenging with an
issues of highly imbalanced class. In the field of data mining, prediction or typically known as …

Low attendance levels in medical appointments have been associated with poor health
outcomes and efficiency problems for service providers. To address this problem, healthcare …

Background Screening for suicidal ideation in high-risk groups such as US veterans is
crucial for early detection and suicide prevention. Currently, screening is based on clinical …

Prediction of diseases is sensitive as any error can result in the wrong person's treatment or
not treating the right patient. Besides, some features distinguish a disease from curable to …

The ability to understand not only that a piece of research has been cited, but why it has
been cited has wide-ranging applications in the areas of research evaluation, in tracking the …

Preterm labor is the leading cause of neonatal morbidity and mortality in newborns and has
attracted significant research attention from many scientific areas. The relationship between …

This study, focusing on identifying rare attacks in imbalanced network intrusion datasets,
explored the effect of using different ratios of oversampled to undersampled data for binary …

Uterine contractions are routinely monitored by tocodynamometer (TOCO) at late stage of
pregnancy to predict the onset of labor. However, TOCO reveals no information on the …

Diagnosing cardiovascular disease (CVD) is a crucial issue in healthcare and research on
machine learning. Machine-learning techniques can predict risk at an early stage of CVD …

Learning to rank~(LTR) is the de facto standard for web search, improving upon classical
retrieval models by exploiting (in) direct relevance feedback from user judgments, interaction …