Background: Cardiovascular disease (CVD) is challenging to diagnose and treat since
symptoms appear late during the progression of atherosclerosis. Conventional risk factors …

The Tehran cardiometabolic genetic study (TCGS) is a large population-based cohort study
that conducts periodic follow-ups. TCGS has created a comprehensive database comprising …

The main goals of this work are to study and compare machine learning algorithms to predict
the development of type 2 diabetes mellitus. Four classification algorithms have been …

Introduction High blood pressure is widely regarded as the most important risk factor for
cardiovascular diseases. Epistasis analysis may provide additional insight into the genetic …

Background Although the inherited risk factors associated with fatty liver disease are well
understood, little is known about the genetic background of metabolic dysfunction …

Diabetes is a chronic disease, which is characterized by abnormally high blood sugar levels.
It may affect various organs and tissues, and even lead to life-threatening complications …

Objective: Metabolic syndrome (MetS) is a complex multifactorial disorder that considerably
burdens healthcare systems. We aim to classify MetS using regularized machine learning …

Teacher evaluation has emerged as a central theme in school reform efforts. Students' rating
decisions are often used by HLI leaders when hiring, promoting, determining tenure, raising …

Abstract The Tehran Cardiometabolic Genetic Study (TCGS) is a large population-based
cohort study with periodic follow-ups, which created a comprehensive database of 20,367 …

Timely detection of patients with a high mortality risk in coronavirus disease 2019 (COVID-
19) can substantially improve triage, bed allocation, time reduction, and potential outcomes …