Latest AI and machine learning research in diabetes for healthcare professionals.
PURPOSE: Stage is an important feature to identify in retinal images of infants at risk of retinopat...
: Over the next 25 years, the global prevalence of diabetes is expected to grow to affect 700 millio...
PURPOSE: To develop a deep learning (DL) system that can detect referable diabetic retinopathy (RDR)...
Thermography enables non-invasive, accessible, and easily repeated foot temperature measurements for...
IgA nephropathy (IgAN) is common worldwide and has heterogeneous phenotypes. Predicting long-term ou...
Our previous research shows that structured cancer DX description data accuracy varied across electr...
Diabetes mellitus, commonly measured through an invasive process which although is accurate, has man...
BACKGROUND: The impending scale up of noncommunicable disease screening programs in low- and middle-...
The current lack of consensus for diagnosing glaucoma makes it difficult to develop diagnostic tests...
(1) Background: the use of machine learning techniques for the purpose of anticipating hypoglycemia ...
The purpose of this study was to introduce a new deep learning (DL) model for segmentation of the fo...
IMPORTANCE: Accurate clinical decision support tools are needed to identify patients at risk for iat...
In this paper, we introduce a network machine learning method to identify potential bioactive anti-C...
Diabetic retinopathy is one of the main causes of blindness in human eyes, and lesion segmentation i...
We identified the prevalence of elevated high-sensitivity C-reactive protein and interleukin-6 in pa...
BACKGROUND: Diabetes mellitus is a prevalent metabolic disease characterized by chronic hyperglycemi...
PURPOSE: Heatmapping techniques can support explainability of deep learning (DL) predictions in medi...
INTRODUCTION: C-peptide is used as a marker of endogenous insulin secretion in the assessment of res...
In this study, we proposed a systems biology approach to investigate the pathogenic mechanism for id...
OBJECTIVE: Gestational diabetes mellitus (GDM) is associated with adverse maternal and fetal outcome...
BACKGROUND: Despite excellent prediction performance, noninterpretability has undermined the value o...