AIMC Topic: Diabetes Mellitus, Type 2

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Properties of AgNPs stabilized with polyvinylpyrrolidone relevant to antidiabetic agents.

Nanoscale
Type 2 diabetes mellitus (DM2) is a chronic metabolic disease. Silver nanoparticles (AgNPs) show promise in their treatment. This study assessed the potential of AgNPs as DM2 treatment agent using in vitro, in vivo, and machine learning approaches. M...

PODiaCarD: a prototype of a digital twin platform for the management of pediatric obesity and related cardiometabolic complications.

European journal of pediatrics
UNLABELLED: Childhood obesity is the main driver of early metabolic risk, predisposing to cardiovascular disease (CVD) and type 2 diabetes (T2D), which cause millions of deaths worldwide. Their progression is influenced by biological, behavioral, and...

Machine Learning Analysis of Retrospective Data From 503 Hospitalized Older Patients With Type 2 Diabetes to Identify Factors Associated With Cognitive Impairment.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Diabetes is increasingly prevalent among older adults; mild cognitive impairment (MCI) comorbidity in this group represents a major concern. Existing MCI prediction methods are often inaccurate, but machine learning (ML) offers improved po...

Fostering Multidisciplinary Collaboration in Artificial Intelligence and Machine Learning Education: Tutorial Based on the AI-READI Bootcamp.

JMIR medical education
BACKGROUND: The integration of artificial intelligence (AI) and machine learning (ML) into biomedical research requires a workforce fluent in both computational methods and clinical applications. Structured, interdisciplinary training opportunities r...

Intelligent glucose management in hospitalized patients: Short-term glucose and adverse events prediction.

PloS one
The management of blood glucose in hospitalized patients is confined to retrospective interventions, preventing healthcare professionals from predicting patients' blood glucose levels and potential adverse events in advance. This study employs a deep...

Circulating long non-coding RNAs as predictors of type 2 diabetes mellitus development: results from the CORDIOPREV study.

Cardiovascular diabetology
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a growing global health challenge. Conventional diagnostic tools have limited sensitivity and specificity for early-stage disease. In this context, long non-coding RNAs (lncRNAs) have emerged as promisin...

The effects of physical activity on diabetic retinopathy in type 2 diabetes using automated vascular analysis: a cohort study.

Journal of global health
BACKGROUND: Evidence regarding the association between physical activity (PA) and diabetic retinopathy (DR) remains inconsistent. Furthermore, its effects on retinal vessel diameters in type 2 diabetes are not well established. We aimed to investigat...

Efficacy of FiberMore, an AI-Based mHealth Intervention to Increase Dietary Fiber Intake Among Type 2 Diabetes Patients: Protocol for a Pilot Randomized Controlled Trial.

JMIR research protocols
BACKGROUND: A high intake of dietary fiber has been shown to improve glycemic control and decrease hyperinsulinemia in people living with type 2 diabetes (T2D). T2D patients in Japan consume less than the recommended amount of fiber. Based on finding...

Artificial intelligence-based diagnosis of diabetic kidney disease using urinary VOC biosensor data.

BMC nephrology
BACKGROUND: Diabetic kidney disease (DKD) remains a leading cause of chronic kidney disease worldwide. However, current diagnostic methods rely on indirect biomarkers or invasive renal biopsy. This study aimed to evaluate the feasibility of urinary v...

Opportunistic screening of type 2 diabetes with deep metric learning using electronic health records.

Scientific reports
Deep learning models leveraging electronic health records (EHR) for opportunistic screening of type 2 diabetes (T2D) can improve current practices by identifying individuals who may need further glycemic testing. Accurate onset prediction and subtypi...