AIMC Topic: Diabetes Mellitus, Type 2
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Urinary Complement proteome strongly linked to diabetic kidney disease progression.
Nature communications
Aug 7, 2025
Diabetic kidney disease (DKD) progression is not well understood. Using high-throughput proteomics, biostatistical, pathway and machine learning tools, we examine the urinary Complement proteome in two prospective cohorts with type 1 or 2 diabetes an...
Exhaled gas biomarkers: a non-invasive approach for distinguishing diabetes and its complications.
The Analyst
Aug 4, 2025
Exhaled gas detection offers a safe, convenient, and non-invasive clinical diagnostic method for preventing the progression of diabetes to complications. In this study, gas chromatography-mass spectrometry (GC-MS) analysis and statistical methods wer...
Association between air pollution and type II diabetes in Italy from clinical data and population-weighted exposure at the municipality level.
Scientific reports
Aug 3, 2025
A growing body of literature supports the association between ambient particulate pollution and the risk of type 2 diabetes (T2DM). Both issues are particularly relevant in Italy. This study investigates the relationship between T2DM and exposure to ...
Conditional universal differential equations capture population dynamics and interindividual variation in c-peptide production.
NPJ systems biology and applications
Jul 31, 2025
Universal differential equations (UDEs) are an emerging approach in biomedical systems biology, integrating physiology-driven mathematical models with machine learning for data-driven model discovery in areas where knowledge of the underlying physiol...
A multimodal deep learning architecture for predicting interstitial glucose for effective type 2 diabetes management.
Scientific reports
Jul 29, 2025
The accurate prediction of blood glucose is critical for the effective management of diabetes. Modern continuous glucose monitoring (CGM) technology enables real-time acquisition of interstitial glucose concentrations, which can be calibrated against...
Transfer learning prediction of type 2 diabetes with unpaired clinical and genetic data.
Scientific reports
Jul 29, 2025
The prevalence of type 2 diabetes mellitus (T2DM) in Korea has risen in recent years, yet many cases remain undiagnosed. Advanced artificial intelligence models using multi-modal data have shown promise in disease prediction, but two major challenges...
Interpretable machine learning-guided single-cell mapping deciphers multi-lineage pancreatic dysregulation in type 2 diabetes.
Cardiovascular diabetology
Jul 24, 2025
BACKGROUND: Pancreatic cellular heterogeneity is fundamental to systemic metabolic regulation, yet its pathological remodeling in diabetes remains poorly characterized.
Machine learning driven diabetes care using predictive-prescriptive analytics for personalized medication prescription.
Scientific reports
Jul 23, 2025
The increasing prevalence of type 2 diabetes (T2D) is a significant health concern worldwide. Effective and personalized treatment strategies are essential for improving patient outcomes and reducing healthcare costs. Machine learning (ML) has the po...
AI-Driven segmentation and morphogeometric profiling of epicardial adipose tissue in type 2 diabetes.
Cardiovascular diabetology
Jul 18, 2025
BACKGROUND: Epicardial adipose tissue (EAT) is associated with cardiometabolic risk in type 2 diabetes (T2D), but its spatial distribution and structural alterations remain understudied. We aim to develop a shape-aware, AI-based method for automated ...
Predicting postprandial glucose excursions to personalize dietary interventions for type-2 diabetes management.
Scientific reports
Jul 17, 2025
Elevated postprandial glucose levels present a global epidemic and a major challenge in type-2 diabetes (T2D) management. A key barrier to developing effective dietary interventions for T2D management is the wide inter-individual variation in glycemi...
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