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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. - Includes Artificial intelligence (AI) data for the prediction, diagnosis, treatment, and prognostication for diabetes as a model disease - Describes the most important issues of our time that comprise the most important technologies currently being applied to diabetes - Presented in a consistent easy to help those new to the field understand and compare/contrast various elements of digital health, telehealth, and artificial intelligence for diabetes
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Diabetes Digital Health brings together the multifaceted information surrounding the science of digital health from an academic, regulatory, industrial, investment and cybersecurity perspective. Clinicians and researchers who are developing and evaluating mobile apps for diabetes patients will find this essential reading, as will industry people whose companies are developing mobile apps and sensors. - Provides valuable information for clinicians, researchers and industry about the design and evaluation of patient-facing diabetes adherence technologies - Highlights cutting-edge topics that are presented and discussed at the Digital Diabetes Congress
Diabetes Digital Health and Telehealth explains, from technologic, economic and sociologic standpoints how digital health and telehealth have come to dominate the management of diabetes. The book also includes information on improved telemedicine tools and platforms for communicating with patients, reviewing medical records, and interpreting data from wearable devices. In addition, evolving wearable sensors such as continuous glucose monitors, closed loop automated insulin delivery systems, cuffless blood pressure monitors, exercise monitors and smart insulin pens are covered. - Covers advances in the fields of digital health and telehealth, including research methods, relevant types of evidence, and viable endpoints for assessing the clinical and economic benefits of digital health and telehealth for diabetes - Discusses improved telemedicine tools and platforms for communicating with patients, reviewing medical records and interpreting data from wearable devices - Analyzes information gaps, research methods, relevant types of evidence, and viable endpoints for assessing the clinical and economic benefits of digital health and telehealth for diabetes
AI is poised to transform every aspect of healthcare, including the way we manage personal health, from customer experience and clinical care to healthcare cost reductions. This practical book is one of the first to describe present and future use cases where AI can help solve pernicious healthcare problems. Kerrie Holley and Siupo Becker provide guidance to help informatics and healthcare leadership create AI strategy and implementation plans for healthcare. With this book, business stakeholders and practitioners will be able to build knowledge, a roadmap, and the confidence to support AIin their organizations—without getting into the weeds of algorithms or open source frameworks. Cowritten by an AI technologist and a medical doctor who leverages AI to solve healthcare’s most difficult challenges, this book covers: The myths and realities of AI, now and in the future Human-centered AI: what it is and how to make it possible Using various AI technologies to go beyond precision medicine How to deliver patient care using the IoT and ambient computing with AI How AI can help reduce waste in healthcare AI strategy and how to identify high-priority AI application
Telemedicine Technologies: Big Data, Deep Learning, Robotics, Mobile and Remote Applications for Global Healthcare illustrates the innovative concepts, methodologies and frameworks that will increase the feasibility of the existing telemedicine system. The book also focuses on showcasing prototypes of remote healthcare systems, thus emphasizing the data processing side that is often recognized as the backbone of any telemedicine system. - Illustrates the innovative concepts, methodologies and frameworks that will increase the feasibility of the existing telemedicine system - Focuses on showcasing prototypes of remote healthcare systems
Artificial intelligence models are being used to make labor and delivery safer for mothers and newborns. Sensors are exploited to gauge health parameters, and machine learning techniques are investigated to predict the health conditions of patients to assist medical practitioners. This is a critical area of study as maternal and infant health are indispensable for a healthy society. Predicting Pregnancy Complications Through Artificial Intelligence and Machine Learning considers the recent advances, challenges, and best practices of artificial intelligence and machine learning in relation to pregnancy complications. Covering key topics such as pregnancy complications, wearable sensors, and healthcare technologies, this premier reference source is ideal for nurses, doctors, computer scientists, medical professionals, industry professionals, researchers, academicians, scholars, instructors, and students.
A multidisciplinary approach to the latest developments of nanomedicine for the treatment of different facets of diabetes.
This book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology. Expertly written chapters examine AI in age-related macular degeneration, glaucoma, retinopathy of prematurity and diabetic retinopathy screening. AI perspectives, systems and limitations are all carefully assessed throughout the book as well as the technical aspects of DL systems for retinal diseases including the application of Google DeepMind, the Singapore algorithm, and the Johns Hopkins algorithm. Artificial Intelligence in Ophthalmology meets the need for a resource that reviews the benefits and pitfalls of AI, ML and DL in ophthalmology. Ophthalmologists, optometrists, eye-care workers, neurologists, cardiologists, internal medicine specialists, AI engineers and IT specialists with an interest in how AI can help with early diagnosis and monitoring treatment in ophthalmic patients will find this book to be an indispensable guide to an evolving area of healthcare technology.
Neurological Modulation of Sleep provides readers with updated scientific reviews regarding the interaction between sleep and contributing factors, with special attention paid to the potential for neurological modulation of sleep via diet. This book expands the notion of diet and adds an element of physical activity and exercise as well as a chapter on caffeine and its effects on sleep. With 30+ international contributors, this book aims to provide readers with a unique global perspective on the role these factors plays in sleep architecture and its regulation by circadian biology and neurology. Sleep disorders have become an increasing problem plaguing more than 70 million Americans according to the American Sleep Association. There is a clear association between sleep disorder and a wide range of other human disorders –performance deficiencies, psychiatric illnesses, heart disease, obesity and more – but in spite of this there is not yet a convenient overview on the market detailing the impact of obesity, age, diabetes and diet on sleep duration and attendant health outcomes. - Describes the impact of diet, caffeine and physical activity on sleep - Reviews the neurology and metabolism of sleep - Identifies what foods impact sleep and how - Discusses the clinical use of nutraceuticals to improve sleep