Latest AI and machine learning research in diabetes for healthcare professionals.
Previously published photoplethysmography-(PPG) based non-invasive blood glucose (NIBG) measurements...
Organotypic brain slice models are an ideal technological platform to investigate therapeutic option...
Various factors influencing postoperative incisional infection in gynecologic tumors were analyzed, ...
An unsolved challenge in the development of antigen-specific immunotherapies is determining the opti...
AIMS: Gestational diabetes (GDM) is the most common metabolic disorder of pregnancy, requiring compl...
BACKGROUND: The aim of the present paper is to construct an emulator of a complex biological system ...
BACKGROUND: Among patients with type 2 diabetes, minority racial/ethnic groups have a higher burden ...
BACKGROUND: Doctors can detect symptoms of diabetic retinopathy (DR) early by using retinal ophthalm...
Obesity is one of the main drivers of type 2 diabetes, but it is not uniformly associated with the d...
INTRODUCTION: Type 1 diabetes mellitus (T1DM) is one of the most frequent autoimmune diseases in chi...
While the construction of a dependable force field for performing classical molecular dynamics (MD) ...
Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surp...
IMPORTANCE: Diabetic retinopathy (DR) is a leading cause of blindness in adults worldwide. Early det...
Dipeptidyl peptidase-4 (DPP-4) inhibitors are becoming an essential drug in the treatment of type 2 ...
PURPOSE: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness related to oxyge...
Type 2 diabetes is a chronic, costly disease and is a serious global population health problem. Yet,...
The stage and duration of hypertension are connected to the occurrence of Hypertensive Retinopathy (...
INTRODUCTION: Oxidative stress is crucial in diabetic pathophysiology, hence the prerequisite of ing...
Data-driven characterization of symptom clusters in chronic conditions is essential for shared clust...
BACKGROUND: Medical experts in the domain of Diabetes Mellitus (DM) acquire specific knowledge from ...
PURPOSE: To evaluate the performance of a federated learning framework for deep neural network-based...