Background Diabetes is a public health problem worldwide. Although diabetes is a chronic
and incurable disease, measures and treatments can be taken to control it and keep the …

Data mining and machine learning algorithms' performance is degraded by data of high-
dimensional nature due to an issue called “curse of dimensionality”. Feature selection is a …

Recommender systems use different techniques of machine learning (ML) to suggest users
and recommend service or entity in various field of application such as in health care …

Background: Hospitals face a significant problem meeting patients' medical needs during
epidemics, especially when the number of patients increases rapidly, as seen during the …

Large blocks of data must be analyzed and explored by utilizing the data mining procedures
in order to uncover significant patterns and trends. Medical databases are one area where …

The recommender system filters out important information from a large pool of information to
set some important decisions in terms of recommendation. It has had an impact in almost …

Background: Health recommender systems (HRSs) are intelligent systems that can be used
to tailor digital health interventions. We compared two HRSs to assess their impact providing …

Cervical cancer poses a significant global health concern, and machine learning techniques
have shown great promise in early detection and diagnosis. However, the dominant focus …

Recommendation system plays a vital role in all fields in the current situation. It enables the
prediction of the link between the independent compounds. In the health care domain, the …

With the advancement in the technology sector spanning over every field, a huge influx of
information is inevitable. Among all the opportunities that the advancements in the …