Internet of Things and Machine Learning for Type I and Type II Diabetes 1st Edition

Capture the future of diabetes care with Internet of Things and Machine Learning for Type I and Type II Diabetes, 1st Edition by Sujata Dash, Subhendu Kumar Pani, Willy Susilo, Cheung Man Yung Bernard, and Gary Tse. This authoritative guide blends cutting-edge IoT architectures with advanced machine learning to transform how clinicians, engineers, and data scientists approach both Type I and Type II diabetes management.

Discover practical frameworks for integrating wearable sensors, continuous glucose monitors, and mobile health platforms into scalable systems that support remote monitoring, real-time alerts, and personalized insulin or lifestyle recommendations. Clear explanations of predictive modeling, anomaly detection, feature engineering, and model deployment make complex concepts accessible—without sacrificing technical rigor.

Designed for healthcare professionals, researchers, and technology developers across North America, Europe, Asia-Pacific, and beyond, this edition emphasizes real-world implementation: data privacy and security best practices, regulatory considerations, interoperability standards, and case studies demonstrating improved patient outcomes. Learn how to turn time-series data into actionable insights, reduce hypoglycemic events, and enable proactive care pathways across hospital networks and community health settings.

If you’re building smarter diabetes solutions or evaluating digital health investments, this book delivers a roadmap from prototype to production. Practical, evidence-based, and globally relevant, it positions you at the intersection of IoT innovation and clinical excellence.

Equip your team or library with a forward-looking reference that advances diabetes care through technology. Order Internet of Things and Machine Learning for Type I and Type II Diabetes today and lead the shift toward data-driven, patient-centered diabetes management.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.