The integration of artificial intelligence and machine learning in diabetes care is transforming disease management through predictive analytics and automated decision-making. Machine learning algorithms analyze vast datasets to identify early signs of diabetes, optimize insulin dosing, and personalize treatment strategies. AI-driven digital platforms enhance real-time glucose monitoring, allowing for proactive intervention in glycemic fluctuations. Advanced neural networks are being utilized to detect complications such as diabetic retinopathy with high precision. Automated insulin delivery systems, guided by AI, improve time-in-range outcomes, reducing the risk of hypoglycemia. As technology continues to evolve, AI-powered tools are set to enhance patient engagement, streamline clinical workflows, and refine therapeutic interventions for more effective diabetes care.










Title : Vascular health with glucagon-like peptide-1 receptor agonists
Mahir Khalil Ibrahim Jallo, Thumbay University Hospital
Title : The prowess of Overripe Banana Sweetener (OBS) in enhancing nutritive values in food and ameliorating glycaemic responses in type 2 diabetes mellitus
Wan Rosli Wan Ishak, Universiti Sains Malaysia
Title : An intelligent hierarchical medical platform established upon high-quality datasets improves the effectiveness of glycemic management for patients across different levels of hospitals
Zhiheng Zhou, Southern Medical University
Title : Diabetes pathogenesis and prevention
Madhu S Malo, Stapgen LLC
Title : Effects of a structured education program on glycemic control in type 1 diabetes
Ana Paula Franco Pacheco, Estacio University of Brasília
Title : Differential diagnosis of diabetes in young and prevalence of LADA and LADY in young persons attending tertiary diabetes institute in Bengaluru, India
R Anil Kumar, Karnataka Institute of Endocrinology and Research
Title : Association between diabetes technology use and prevalent macrovascular disease in adults with type 1 diabetes: A cross-sectional analysis
Divanshi Trivedi, London Northwest Hospital NHS Foundation Trust
Title : Endocrine-specific diabetes risk modeling, glucose–insulin dynamics, and simulation-based metabolic review using the BVidAL clinical software suite
Abhishek Bansal, New Era Consultancy Services
Title : Using a multi-disciplinary clinic model to prevent diabetic foot ulcer recurrence
Kaishi Yang, Albert Einstein College of Medicine
Title : Shaping the future of diabetes care: New advancements in treatment, digital health and personalized patient care
Rupesh K Gautam, Amity Institute of Pharmacy