Latest AI and machine learning research in diabetes for healthcare professionals.
TOPIC: Diagnostic performance of deep learning-based algorithms in screening patients with diabetes for diabetic retinopathy (DR). The algorithms were compared with the current gold standard of classification by human specialists.
Presence of exudates on a retina is an early sign of diabetic retinopathy, and automatic detection of these can improve the diagnosis of the disease. Convolutional Neural Networks (CNNs) have been used for automatic exudate detection, but with poor performance. This study has investigated different deep learning techniques to maximize the sensitivity and specificity. We have compared multiple deep...
AIMS: Recently, it was suggested that betatrophin has a role in controlling pancreatic β cell proliferation and lipid metabolism, however, its role in...
AIMS: Recent studies have implicated possible contribution of adipocytokines in development and progression of microvascular complications in patients...
Disease diagnosis from medical images has become increasingly important in medical science. Abnormality identification in retinal images has become a ...
Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global interest in recent years. DL has been widely adopted in image r...
PURPOSE: To estimate prevalence and severity of diabetic retinopathy (DR) among U.S. adults with diabetes and with or without chronic kidney disease (...
BACKGROUND AND OBJECTIVE: Diabetic retinopathy (DR) is the most prevalent microvascular complication of diabetes mellitus and can lead to irreversible...
OBJECTIVE: Metformin is the preferred first-line medication for management of type 2 diabetes and prediabetes. However, over a third of patients exper...
BACKGROUND AND OBJECTIVE: In healthcare systems, the cost of unplanned readmission accounts for a large proportion of total hospital payment. Hospital...
AIM: To evaluate the association between high triglyceride/HDL-cholesterol (TG/HDL-C) ratio and insulin resistance (IR) or hyperinsulinemia after oral...
BACKGROUND Aryl-carbon receptor (AhR), a ligand-activated transcription factor, is best known for its ability to mediate the effects of environmental ...
An estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and yet 1 in 2 persons remain undiagnos...
OBJECTIVE: To evaluate the basal/total ratio of daily insulin dose (b/T) in outpatients with diabetes type 1 (DM1) and type 2 (DM2) on basal-bolus reg...
Artificial intelligence (AI) has emerged as a major frontier in computer science research. Although AI has broad application across many medical field...
AIMS: Data from the EDITION 3 randomized study and the Clinformatics claims database were analysed to determine whether insulin glargine 300 U/mL (Gla...
Obesity is increasingly prevalent and associated with increased risk of developing type 2 diabetes, cardiovascular diseases, and cancer. Magnetic reso...
Digital medicine, digital research and artificial intelligence (AI) have the power to transform the field of diabetes with continuous and no-burden re...
AIM: To assess the association between elevated triglycerides/glucose index (TGI) and insulin resistance (IR) or hyperinsulinemia after oral glucose t...
Diabetic Retinopathy (DR) has been a leading cause of blindness in case of human beings falling between the ages of 20 and 74 years. This will have a ...