Diabetes Digital Health, Telehealth, and Artificial Intelligence explains how to develop and use the emerging technologies of digital health, telehealth, and artificial intelligence to address this important public health problem to deliver new hardware, software, and processes. The book explores trends in developing and deploying the three most important emerging technologies for diabetes: digital health, telehealth, and artificial intelligence. This book is essential to clinicians, scientists, engineers, industry professionals, regulators, and investors, offering the tools that will be used to create the next generation products to support a precision medicine approach to manage diabetes. According to the CDC, in the US there are 37 million people with diabetes and 96 million people with prediabetes. Diabetes triples the risk of myocardial infarction and stroke and is the leading cause of blindness, end stage renal failure, and amputations. The management of diabetes is becoming increasingly dominated by digital health tools consisting of wearable sensors, mobile applications providing decision support software, and wireless communication tools. Digital health provides new data streams that can be combined to create unique approaches for diabetes based on a precision medicine paradigm.
1. Chapter 20 : Introduction to Artificial Intelligence in Diabetes - p. Page 244 2. Chapter 21 : Ethics and Fairness for Diabetes Artificial Intelligence - p. Page 260 3. Chapter 22 : Artificial Intelligence to Support Self-management and Coaching - p. Page 273 4. Chapter 23 : Predicting Glucotypes in Prediabetes via Wearables and Artificial Intelligence - p. Page 285 5. Chapter 24 : Tele-ophthalmology for Diabetic Retinopathy - p. Page 300 6. Chapter 25 : Review of Advancements in Noninvasive Detection Techniques of Foot Complications Due to Diabetes - p. Page 311 7. Chapter 26 : Artificial Intelligence in Automated Hormone Delivery - p. Page 326 8. Chapter 27 : Natural Language Processing for Diabetes Digital Health - p. Page 339 9. Chapter 28 : Artificial Intelligence for Diabetes in the Hospital - p. Page 349 10. Index - p. Page 364
Diabetes Digital Health, Telehealth, and Artificial Intelligence explains how to develop and use the emerging technologies of digital health, telehealth, and artificial intelligence to address this important public health problem to deliver new hardware, software, and processes. The book explores trends in developing and deploying the three most important emerging technologies for diabetes: digital health, telehealth, and artificial intelligence. This book is essential to clinicians, scientists, engineers, industry professionals, regulators, and investors, offering the tools that will be used to create the next generation products to support a precision medicine approach to manage diabetes. According to the CDC, in the US there are 37 million people with diabetes and 96 million people with prediabetes. Diabetes triples the risk of myocardial infarction and stroke and is the leading cause of blindness, end stage renal failure, and amputations. The management of diabetes is becoming increasingly dominated by digital health tools consisting of wearable sensors, mobile applications providing decision support software, and wireless communication tools. Digital health provides new data streams that can be combined to create unique approaches for diabetes based on a precision medicine paradigm.
1. Chapter 20 : Introduction to Artificial Intelligence in Diabetes - p. Page 244 2. Chapter 21 : Ethics and Fairness for Diabetes Artificial Intelligence - p. Page 260 3. Chapter 22 : Artificial Intelligence to Support Self-management and Coaching - p. Page 273 4. Chapter 23 : Predicting Glucotypes in Prediabetes via Wearables and Artificial Intelligence - p. Page 285 5. Chapter 24 : Tele-ophthalmology for Diabetic Retinopathy - p. Page 300 6. Chapter 25 : Review of Advancements in Noninvasive Detection Techniques of Foot Complications Due to Diabetes - p. Page 311 7. Chapter 26 : Artificial Intelligence in Automated Hormone Delivery - p. Page 326 8. Chapter 27 : Natural Language Processing for Diabetes Digital Health - p. Page 339 9. Chapter 28 : Artificial Intelligence for Diabetes in the Hospital - p. Page 349 10. Index - p. Page 364
