Objective Insulin plays a central role in the regulation of energy and glucose homeostasis,
and insulin resistance (IR) is widely considered as the “common soil” of a cluster of …

Background Insulin resistance (IR) is associated with diabetes mellitus, cardiovascular
disease (CV), and mortality. Few studies have used machine learning to predict IR in the …

Abstract Model-based glycemic control (GC) protocols are used to treat stress-induced
hyperglycaemia in intensive care units (ICUs). The STAR (Stochastic-TARgeted) glycemic …

Background Opportunely screening for diabetes is crucial to reduce its related morbidity,
mortality, and socioeconomic burden. Machine learning (ML) has excellent capability to …

This paper presents an intelligent healthcare framework by incorporating modern computing
technologies like machine learning and deep learning. The sole motivation of this paper is to …

The data was from the National Health and Nutrition Examination Survey (2007–2018). The
study subjects were 2084 nondiabetic women aged 45–64. The analysis included 48 …

Background. An estimated 425 million people globally have diabetes, accounting for 12% of
the world's health expenditures, and the number continues to grow, placing a huge burden …

Recently, machine learning (ML) applications have received attention in diabetes and
metabolism research. This review briefly provides the basic concepts of ML and specific …

T2DM is a large challenge because it's predicted to affect 693 million people by 2045. There
is currently no simple or non-invasive method to measure and quantify insulin resistance …

Background: Insulin resistance is a common etiology of metabolic syndrome, but receiver
operating characteristic (ROC) curve analysis shows a weak association in Koreans. Using …