Latest AI and machine learning research in diabetes for healthcare professionals.
The adoption of standardized imaging protocols in retinal imaging is critical to overcoming challenges posed by fragmented data formats across devices and manufacturers. The lack of standardization hinders clinical interoperability, collaborative research, and the development of artificial intelligence (AI) models that depend on large, high-quality datasets. The Digital Imaging and Communication i...
This systematic review aims to assess the effectiveness of AI-Driven Decision Support Systems in improving glycemic control, measured by Time in Range (TIR) and HbA1c levels, in patients with diabetes. Included studies were randomized controlled trials (RCTs) that evaluated AI interventions in diabetes management. Exclusion criteria included non-English studies, non-peer-reviewed articles. Studies...
New methods of CGM data analysis are emerging that are valuable for interpreting CGM patterns and underlying metabolic physiology. These new methods...
While continuous glucose monitoring (CGM) has revolutionized metabolic health management, widespread adoption remains limited by cost constraints and ...
Although machine learning is frequently used in medicine for predictive purposes, its accuracy in diabetes-related amputation (DRA) remains unclear. F...
Diabetic macular edema (DME) significantly contributes to visual impairment in diabetic patients. Treatment responses to intravitreal therapies vary...
INTRODUCTION: Risk assessment for high-risk populations is critical for preventing Type 2 Diabetes Mellitus (T2DM). Although China's public health ser...
BACKGROUND: Diabetes has emerged as a critical global public health crisis. Prediabetes, as the transitional phase with 5%-10% annual progression to d...
The potential for continuous non-invasive blood glucose monitoring has attracted a lot of interest in the field of medical diagnostics. This paper pro...
BACKGROUND: Stress hyperglycemia ratio (SHR) and glycemic variability (GV) reflect acute glucose elevation and fluctuations, which correlate with adve...
Several large analyses have revealed contradictory results regarding the association between prostate cancer (PC) survival and the use of statins pres...
This study presents a web-based interactive health risk prediction tool designed to assess diabetes risk using machine learning models. Built on the...
The comorbidities of hypertension impose a heavy burden on patients and society. Early identification is necessary to prompt intervention, but it re...
OBJECTIVE: This study validated the artificial intelligence (AI)-based algorithm LuxIA for screening more-than-mild diabetic retinopathy (mtmDR) from ...
The Hillel Yaffe Age Related Macular Degeneration (HYAMD) dataset is a longitudinal collection of 1,560 Digital Fundus Images (DFIs) from 325 patien...
BACKGROUND: People living with chronic diseases are increasingly seeking health information online. For individuals with diabetes, traditional educati...
Traditional Chinese medicine, as an essential component of traditional medicine, contains active ingredients that serve as a crucial source for mode...
Digital diabetes management technologies (DDMTs) have emerged as promising tools for improving glycemic control in patients with type 2 diabetes melli...
BACKGROUND: Epstein-Barr virus (EBV) is a ubiquitous herpesvirus that is known to cause infectious mononucleosis and is associated with several autoim...
OBJECTIVE: To develop a prediction model for hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM) in twin pregnancy using...