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.
Yong Xiao Wang
Albany Medical Center, United States
F Buck Willis
IUHS School of Medicine, Saint Kitts and Nevis
Gretchen Holmes
Memorial Hospital at Gulfport, United States
Sujith Rajan
NYU Long Island School of Medicine, United States
Amy Gutman
AdventHealth; Tough Love MD, United States
Paraskevi Theofilou
Hellenic Open University, Greece
Clifford Morris
Kihealth, United StatesSubmit your abstract Today
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F Buck Willis, IUHS School of Medicine, Saint Kitts and Nevis
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Wan Rosli Wan Ishak, Universiti Sains Malaysia, Malaysia
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