Use of Machine Learning to Predict the Incidence of Type 2 Diabetes Among Relatively Healthy Adults: A 10-Year Longitudinal Study in Taiwan.

: The prevalence of diabetes is increasing worldwide, particularly in the Pacific Ocean island nations. Although machine learning (ML) models and data mining approaches have been applied to diabetes research, there was no study utilizing ML models to predict diabetes incidence in Taiwan. We aimed to predict the onset of diabetes in order to raise health awareness, thereby promoting any necessary lifestyle modifications and help mitigate disease burden.

The Potential for High-Priority Care Based on Pain Through Facial Expression Detection with Patients Experiencing Chest Pain.

Background And Objective: Cardiovascular disease (CVD), one of the chronic non-communicable diseases (NCDs), is defined as a cardiac and vascular disorder that includes coronary heart disease, heart failure, peripheral arterial disease, cerebrovascular disease (stroke), congenital heart disease, rheumatic heart disease, and elevated blood pressure (hypertension). Having CVD increases the mortality rate. Emotional stress, an indirect indicator associated with CVD, can often manifest through facial expressions.

Association between severity of diabetic complications and risk of cancer in middle-aged patients with type 2 diabetes.

Aim: Hyperglycemia was found to be associated with an increased risk of cancer in a general population cohort. However, it remains to be established whether the severity of diabetic complications is associated with cancer risk in patients with diabetes.

Materials And Methods: We used the National Health Insurance Research Database from 2000 through 2013, including those with newly diagnosed diabetic patients (n = 616,742).

Biallelic EPB41L3 variants underlie a developmental disorder with seizures and myelination defects.

Erythrocyte membrane protein band 4.1 like 3 (EPB41L3: NM_012307.5), also known as DAL1, encodes the ubiquitously expressed, neuronally enriched 4.