Diabetic foot syndrome is a multifactorial pathology with at least three main etiological
factors, ie, peripheral neuropathy, peripheral arterial disease, and infection. In addition to …

Abstract Context Bile acids (BAs) are pivotal signaling molecules that regulate energy
metabolism and inflammation. Recent epidemiological studies have reported specific …

Diabetes is a chronic metabolic disease characterized by hyperglycemia, the follow-up
management of diabetes patients is mostly in the community, but the relationship between …

The discovery of insulin in 1921–due to the efforts of the Canadian research team based in
Toronto–has been a landmark achievement in the history of medicine. Lives of people with …

Objective To establish an optimal model to predict the teicoplanin trough concentrations by
machine learning, and explain the feature importance in the prediction model using the …

Objective: The aim of this study was to identify the important factors affecting cyclosporine
(CsA) blood concentration and estimate CsA concentration using seven different machine …

OBJECTIVE: COVID-19 infection rapidly spread across the globe and evolved into a
pandemic. Artificial intelligence (AI) has been used to predict the spread of the virus and …

Objectives We develop a model for predicting quetiapine levels in patients with depression,
using machine learning to support decisions on clinical regimens. Methods Inpatients …

Aims This study aimed to establish a prediction model of quetiapine concentration in
patients with schizophrenia and depression, based on real‐world data via machine learning …

Background Being one of the most widespread, pervasive, and troublesome illnesses in the
world, depression causes dysfunction in various spheres of individual and social life …