AIMC Topic: Blood Glucose

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Relationship between C-reactive protein triglyceride glucose index and cardiovascular disease risk: a cross-sectional analysis with machine learning.

BMC medical informatics and decision making
BACKGROUND: Cardiovascular disease (CVD) continues to be a leading cause of disease burden and mortality worldwide. Identifying reliable biomarkers for CVD risk assessment is essential. This study investigates the association between the C-reactive p...

Machine learning glucose forecasting models for septic patients.

Scientific reports
Sepsis-induced glucose fluctuations present major challenges in critical care, underscoring the importance of accurate glucose monitoring and forecasting to improve patient outcomes. This study introduces a suite of forecasting models trained using c...

C-reactive protein-triglyceride glucose index in predicting three-vessel coronary artery disease risk: a retrospective study using machine learning approaches.

Annals of medicine
BACKGROUND: Three-vessel coronary artery disease (TVD) is a severe subtype of coronary heart disease, strongly associated with inflammation and metabolic dysfunction. The C-reactive protein-triglyceride glucose index (CTI), an integrated measure of i...

The association between estimated glucose disposal rate and the prevalence and mortality of chronic kidney disease: a cross-sectional study with linked mortality follow-up.

European journal of medical research
BACKGROUND: Metabolic disorders represented by insulin resistance (IR) are at risk of chronic kidney disease (CKD). Estimated glucose disposal rate (eGDR) reflects IR. The relationship between eGDR and CKD was unclear. This study aimed at discussing ...

Precision integrated identification of predictive first-trimester metabolomics signatures for early detection of gestational diabetes mellitus.

Cardiovascular diabetology
BACKGROUND AND AIM: Gestational diabetes mellitus (GDM), a common pregnancy-related metabolic disorder, often goes undiagnosed until the second trimester, limiting early intervention opportunities. Given the higher prevalence of GDM in India, there i...

Development of a machine learning-based interface for insulin dependency prediction using clinical data.

Scientific reports
Diabetes mellitus is a major global health burden, and early identification of insulin dependency is important for timely intervention. This study developed an artificial intelligence-based diagnostic system using a real-world clinical dataset of 100...

A personalized federated learning-based glucose prediction algorithm for high-risk glycemic excursion regions in type 1 diabetes.

Scientific reports
Continuous glucose monitoring (CGM) devices allow real-time glucose readings leading to improved glycemic control. However, glucose predictions in the lower (hypoglycemia) and higher (hyperglycemia) extremes, referred as glycemic excursions, remain c...