Machine Learning algorithms are profusely demonstrated in innumerable medical
applications for prediction, diagnosis, and recommendations to treat patients in surgical and …

Background Controlling the COVID-19 outbreak in Brazil is a challenge due to the
population's size and urban density, inefficient maintenance of social distancing and testing …

Clinical decision support systems (CDSSs) represent the latest technological transformation
in healthcare for assisting clinicians in complex decision-making. Several CDSSs are …

Early detection of the dysfunction of the cardiac autonomic regulation (CAR) may help in
reducing cannabis-related cardiovascular morbidities. The current study examined the …

The virus responsible for COVID-19 is mutating day by day with more infectious
characteristics. With the limited healthcare resources and overburdened medical …

There are no obvious clinical signs of a silent disease until it causes irreversible damage. As
computerized technologies become more common for early detection of ailments, severity …

Background: Fish is a food ingredient that is consumed throughout the world. When fishes
die, their freshness begins to decrease. The freshness of the fish can be determined by the …

Data categorization is a top concern in medical data to predict and detect illnesses; thus, it is
applied in modern healthcare informatics. In modern informatics, machine learning and …

Chronic kidney disease (CKD), a significant issue for public health, affects millions of
individuals globally. The course of end-stage renal disease must be stopped or reversed …

Background. Primary blepharospasm (BSP) is one of the most common focal dystonia and
its pathophysiological mechanism remains unclear. An unbiased method was used in …