Diabetes

Streamlining the Histopathologic Workflow in Diabetic Kidney Disease with Artificial Intelligence.

KEY POINTS: Artificial intelligence models effectively generalized across studies and animal models and reduced translational gaps when applied to human biopsies. Artificial intelligence assistance reduced study evaluation turnaround times by up to 90% versus manual whole slide imaging scoring, matching expert-level performance. Self-supervised learning captured diabetic kidney disease-relevant fe...

Manipulating starch crystalline structure for controlled digestibility and glycemic response.

Postprandial hyperglycemia is a key driver in the development of type 2 diabetes, and dietary starch is a major modulator of glycemic response. The crystalline structure of starch is a principal determinant of its digestibility and postprandial glycemic response. This review synthesizes evidence establishing that the molecular packing density and stability of A-, B-, and V-type crystals often outw...

Special AAO Report: Recommendations on Screening for Hydroxychloroquine Retinopathy (2025 Revision).

BACKGROUND: The American Academy of Ophthalmology recommendations on screening for hydroxychloroquine (HCQ) retinopathy are now a decade old. This rev...

Association of HbA1c and an updated glucose management indicator (uGMI) with incident diabetic retinopathy in adults with type 1 diabetes: a longitudinal study.

AIMS/HYPOTHESIS: This study aimed to compare the predictive performance of HbA1c and a continuous glucose monitoring (CGM)-based updated glucose manag...

Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.

Chronic kidney disease (CKD) represents a major and expanding global health challenge, with prevalence rising due to aging populations, diabetes, hype...

The Development and Validation of Multivariable Electronic Health Record-Based Models to Predict Diabetic Ketoacidosis-Related Hospitalizations for Adults with Type 1 Diabetes.

AIM: To develop and validate models that use electronic health record (EHR) data to predict diabetic ketoacidosis (DKA)-related hospitalizations over ...

Mapping systemic inter-organ metabolic networks across glycemic continuum using whole-body [18F]FDG PET/CT and machine learning.

PURPOSE: Glucose homeostasis relies on coordinated interactions among multiple organs, and its disruption relates to diabetes development. This study ...

The application of machine learning in the evaluation of urinary tract infections incidence in patients in a Nursing and Treatment Facility.

BACKGROUND: Urinary tract infection (UTI) is a serious problem in the healthcare system. It is caused by bacteria from the gastrointestinal tract. The...

PathViT Model for Automated Disease Classification from Skeletal Muscle Histopathology.

Analyzing skeletal muscle pathology from histological images is labor intensive (requiring manual cell counting, segmentation, and thresholding), time...

Can artificial intelligence and wearable technologies transform diabetes foot health?

PURPOSE OF REVIEW: Diabetes foot ulcers (DFUs) affect millions globally, and are a global health challenge, contributing significantly to morbidity, m...

Construction and validation of a hypertensive nephropathy diagnostic model based on mitochondrial-related genes using machine learning combined with WGCNA.

BACKGROUND: Hypertensive nephropathy (HTN) arises from chronic hypertension and may potentially result in severe renal failure. Due to the absence of ...

Assessing the User Experience of an LLM-Based Conversational Assistant in Diabetes Mellitus Care.

UNLABELLED: This article presents the design, implementation, and evaluation of MarIA, a GPT-3.5-powered virtual assistant integrated into a messaging...

Unraveling Shared Diagnostic Biomarkers: Integrated Bioinformatics Identification of CGB7, MYCNUT, and GPR32 in Gestational Diabetes Mellitus and Retinopathy of Prematurity.

The relationship between Gestational Diabetes Mellitus (GDM) and Retinopathy of Prematurity (ROP) is not fully understood, but both conditions may sha...

Artificial intelligence methods in gestational diabetes mellitus prediction: A systematic literature review.

Gestational diabetes mellitus (GDM) is the most common metabolic disorder in pregnancy, posing risks to both maternal and neonatal health. Artificial ...

Artificial intelligence in obstetrics and gynecology: Evaluating ChatGPT and Google Gemini in answering patient questions.

INTRODUCTION: To evaluate the accuracy and completeness of responses across common obstetrical and gynecologic topics generated by the large language ...

Using precision medicine methods to identify disease stages for chronic limb-threatening ischemia in participants of the BEST-CLI trial.

BACKGROUND: Chronic limb-threatening ischemia (CLTI), the most severe form of peripheral artery disease, is associated with a high risk of limb loss. ...

Association between triglyceride-glucose index and depression and the mediating role of hypertension: a cross-sectional study of obese adults.

BACKGROUND: Recent findings indicate a positive correlation between the TyG (triglyceride-glucose) index and the incidence of depression. However, the...

A Five-Plasma Protein-Based Algorithm for Predicting Incident CKD in Type 2 Diabetes.

KEY POINTS: Proteomics analyses consistently identified nine independent protein predictors for CKD in both Chinese and European participants with typ...

Interpretable type 2 diabetes incidence prediction with AutoScore: A model based on standard clinical parameters.

OBJECTIVE: Accurate prediction of type 2 diabetes mellitus (T2DM) onset is critical to enable timely interventions and preventive strategies. Although...

GPT-4o in Nutrition for Inpatients Undergoing Post-Stroke Rehabilitation: Identifying Dietary Errors, Exploring Expert-AI Rationale Differences, and Structuring AI-Expert Collaboration.

OBJECTIVE: Inpatients undergoing stroke rehabilitation experience high malnutrition rates, requiring strict dietary management. However, manual and ti...