PURPOSE OF REVIEW: Lower extremity amputations (LEAs) are among the most severe complications of diabetes, with approximately 1.5 million procedures performed globally each year. This review explores the impact of social and structural determinants o...
Within the healthcare sector, the application of machine learning is gaining prominence, notably enhancing the efficiency and precision of diagnostic procedures. This study focuses on this key area of diabetes prediction and aims to develop an innova...
The journal of physical chemistry letters
Jun 15, 2025
Accurate and early detection of C-peptide, a stable biomarker indicative of diabetes, is crucial for disease diagnosis, treatment, and prevention. This study explores a novel detection methodology using solid-state nanopore technology coupled with ma...
Journal of agricultural and food chemistry
Jun 5, 2025
The lack of suitable chemical research methodologies has hindered the discovery of rational daily diet combinations from large-scale dietary-derived compounds. Three deep learning models based on chemical properties for α-glucosidase inhibitors (AGIs...
Diabetes Mellitus is a chronic metabolic disorder affecting a substantial global population leading to complications such as retinopathy, nephropathy, neuropathy, foot problems, heart attacks, and strokes if left unchecked. Prompt detection and diagn...
Machine learning is increasingly used to predict lifestyle-related disease onset using health and medical data. However, its predictive accuracy for use is often hindered by dataset shift, which refers to discrepancies in data distribution between th...
BACKGROUND: Diabetes affects millions worldwide. Primary care physicians provide a significant portion of care, and they often struggle with selecting appropriate medications.
BACKGROUND: AI-assisted blood glucose management has become a promising method to enhance diabetes care, leveraging technologies like continuous glucose monitoring (CGM) and predictive models. A comprehensive bibliometric analysis is needed to unders...
BACKGROUND: This study investigated the cost-effectiveness and clinical impact of the 3E model (education, empowerment, and economy) in diabetes management using advanced machine learning techniques.
Chronic diseases are a critical focus in the management of elderly health. Early disease prediction plays a vital role in achieving disease prevention and reducing the associated burden on individuals and healthcare systems. Traditionally, separate m...
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