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Diabetes Mellitus, Type 2

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Mulberry leaves ameliorate diabetes via regulating metabolic profiling and AGEs/RAGE and p38 MAPK/NF-κB pathway.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Mulberry leaves have been used as traditional hypoglycemic medicine-food plant for thousand years in China. According to traditional Chinese medicine theory, type 2 diabetes mellitus (T2DM) belongs to the category of X...

The Importance of Close Follow-Up in Patients with Early-Grade Diabetic Retinopathy: A Taiwan Population-Based Study Grading via Deep Learning Model.

International journal of environmental research and public health
(1) Background: Diabetic retinopathy (DR) can cause blindness. Current guidelines on diabetic eye care recommend more frequent eye examinations for more severe DR to prevent deterioration. However, close follow-up and early intervention at earlier st...

Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction.

Nature communications
A promise of genomics in precision medicine is to provide individualized genetic risk predictions. Polygenic risk scores (PRS), computed by aggregating effects from many genomic variants, have been developed as a useful tool in complex disease resear...

Risk prediction of diabetic nephropathy using machine learning techniques: A pilot study with secondary data.

Diabetes & metabolic syndrome
AIMS: This research work presented a comparative study of machine learning (ML), including two objectives: (i) determination of the risk factors of diabetic nephropathy (DN) based on principal component analysis (PCA) via different cutoffs; (ii) pred...

Deep Learning for Classifying Physical Activities from Accelerometer Data.

Sensors (Basel, Switzerland)
Physical inactivity increases the risk of many adverse health conditions, including the world's major non-communicable diseases, such as coronary heart disease, type 2 diabetes, and breast and colon cancers, shortening life expectancy. There are mini...

Real-world artificial intelligence-based opportunistic screening for diabetic retinopathy in endocrinology and indigenous healthcare settings in Australia.

Scientific reports
This study investigated the diagnostic performance, feasibility, and end-user experiences of an artificial intelligence (AI)-assisted diabetic retinopathy (DR) screening model in real-world Australian healthcare settings. The study consisted of two c...

CAFT: a deep learning-based comprehensive abdominal fat analysis tool for large cohort studies.

Magma (New York, N.Y.)
BACKGROUND: There is increasing appreciation of the association of obesity beyond co-morbidities, such as cancers, Type 2 diabetes, hypertension, and stroke to also impact upon the muscle to give rise to sarcopenic obesity. Phenotypic knowledge of ob...

A New Clinical Utility for Tubular Markers to Identify Kidney Responders to Saxagliptin Treatment in Adults With Diabetic Nephropathy.

Canadian journal of diabetes
OBJECTIVES: In recent clinical studies, saxagliptin exhibited nephroprotective potential by lowering albuminuria. In this study, we aimed to determine whether these kidney effects of saxagliptin were mediated by changes in markers of kidney tubular d...

Generalizability of heterogeneous treatment effects based on causal forests applied to two randomized clinical trials of intensive glycemic control.

Annals of epidemiology
Purpose Machine learning is an attractive tool for identifying heterogeneous treatment effects (HTE) of interventions but generalizability of machine learning derived HTE remains unclear. We examined generalizability of HTE detected using causal fore...