Artificial Intelligence and Machine Learning in Diabetes Care

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.

Committee Members
Speaker at Diabetes 2026 - Mahir Khalil Ibrahim Jallo

Mahir Khalil Ibrahim Jallo

Gulf Medical University, Canada
Speaker at Diabetes 2026 - F Buck Willis

F Buck Willis

Christian College of Medicine, Belize
Speaker at Diabetes 2026 - Anil Harrison

Anil Harrison

Midwestern University, United States
Speaker at Diabetes 2026 - Wan Rosli Wan Ishak

Wan Rosli Wan Ishak

Universiti Sains Malaysia, Malaysia
Diabetes 2026 Speakers
Speaker at Diabetes 2026 - Mahir Khalil Ibrahim Jallo

Mahir Khalil Ibrahim Jallo

Gulf Medical University, Canada
Speaker at Diabetes 2026 - F Buck Willis

F Buck Willis

Christian College of Medicine, Belize
Speaker at Diabetes 2026 - Anil Harrison

Anil Harrison

Midwestern University, United States
Speaker at Diabetes 2026 - David Navazio

David Navazio

Gentell, United States
Speaker at Diabetes 2026 - Sujith Rajan

Sujith Rajan

NYU Long Island School of Medicine, United States
Speaker at Diabetes 2026 - David Petch

David Petch

utR Biotech, Canada
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