The management of movement disorders is undergoing rapid transformation through the use of innovative health technologies, such as wearable sensors, mobile apps, robotics, and telemedicine systems. These technologies continue to evolve, providing new solutions for early diagnosis, remote monitoring, tailored treatments, and enhanced rehabilitative strategies that cater to individual needs through personalized approaches. With the aid of new health technologies, motor abnormalities can be sensitively recognized and objectively assessed, providing quantifiable measures to detect subtle changes associated with treatment response and disease progression. Moreover, long-term instrumental monitoring offers the opportunity for improving therapeutic strategies by gathering ecological data directly at patients’ homes in free-living situations.

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

Wearable Technology in Medicine and Health Care provides readers with the most current research and information on the clinical and biomedical applications of wearable technology. Wearable devices provide applicability and convenience beyond many other means of technical interface and can include varying applications, such as personal entertainment, social communications and personalized health and fitness. The book covers the rapidly expanding development of wearable systems, thus enabling clinical and medical applications, such as disease management and rehabilitation. Final chapters discuss the challenges inherent to these rapidly evolving technologies. - Provides state-of-the-art coverage of the latest advances in wearable technology and devices in healthcare and medicine - Presents the main applications and challenges in the biomedical implementation of wearable devices - Includes examples of wearable sensor technology used for health monitoring, such as the use of wearables for continuous monitoring of human vital signs, e.g. heart rate, respiratory rate, energy expenditure, blood pressure and blood glucose, etc. - Covers examples of wearables for early diagnosis of diseases, prevention of chronic conditions, improved clinical management of neurodegenerative conditions, and prompt response to emergency situations

Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on artificial intelligence (AI), its link to precision medicine (PM), and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as AI has gained significant attention during the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems have enabled the generation of large datasets, making autoimmunity an ideal target for AI and precision medicine. More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large datasets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. - Allows the readers to gain an overview on precision medicine for autoimmune diseases leveraging AI solutions - Provides background, milestone and examples of precision medicine - Outlines the paradigm shift towards precision medicine driven by value-based systems - Discusses future applications of precision medicine research using AI - Other aspects covered in the book include regulatory insights, data analytics and visualization, types of biomarkers as well as the role of the patient in precision medicine

More than ten million patients now travel abroad every year for affordable, high-quality healthcare. From Thailand's American-accredited Bumrungrad International Hospital to Eric Clapton's Crossroads Center in Antigua to Johns Hopkins International Medical Center in Singapore, health travelers now have access to a full array of the world's safest, best choices in healthcare facilities and physicians. Now in its Third Edition, Patients Beyond Borders remains the best-read, most comprehensive, easy-to-understand guide to medical tourism, written by the world's leading spokesperson on international health travel. Patients Beyond Borders Third Edition lists the 25 top medical travel destinations, where patients can choose from hundreds of hospitals and save 30-80% on medical procedures, ranging from a comprehensive health check-up to heart work, orthopedics, dental and cosmetic surgery, in vitro fertilization and more.

Prolonged life expectancy along with the increasing complexity of medicine and health services raises health costs worldwide dramatically. Whilst the smart health concept has much potential to support the concept of the emerging P4-medicine (preventive, participatory, predictive, and personalized), such high-tech medicine produces large amounts of high-dimensional, weakly-structured data sets and massive amounts of unstructured information. All these technological approaches along with “big data” are turning the medical sciences into a data-intensive science. To keep pace with the growing amounts of complex data, smart hospital approaches are a commandment of the future, necessitating context aware computing along with advanced interaction paradigms in new physical-digital ecosystems. The very successful synergistic combination of methodologies and approaches from Human-Computer Interaction (HCI) and Knowledge Discovery and Data Mining (KDD) offers ideal conditions for the vision to support human intelligence with machine learning. The papers selected for this volume focus on hot topics in smart health; they discuss open problems and future challenges in order to provide a research agenda to stimulate further research and progress.

What happens when people turn their everyday experience into data: an introduction to the essential ideas and key challenges of self-tracking. People keep track. In the eighteenth century, Benjamin Franklin kept charts of time spent and virtues lived up to. Today, people use technology to self-track: hours slept, steps taken, calories consumed, medications administered. Ninety million wearable sensors were shipped in 2014 to help us gather data about our lives. This book examines how people record, analyze, and reflect on this data, looking at the tools they use and the communities they become part of. Gina Neff and Dawn Nafus describe what happens when people turn their everyday experience—in particular, health and wellness-related experience—into data, and offer an introduction to the essential ideas and key challenges of using these technologies. They consider self-tracking as a social and cultural phenomenon, describing not only the use of data as a kind of mirror of the self but also how this enables people to connect to, and learn from, others. Neff and Nafus consider what's at stake: who wants our data and why; the practices of serious self-tracking enthusiasts; the design of commercial self-tracking technology; and how self-tracking can fill gaps in the healthcare system. Today, no one can lead an entirely untracked life. Neff and Nafus show us how to use data in a way that empowers and educates.

Inside today's data-driven personalized medicine, and the time, effort, and information required from patients to make it a reality Medicine has been personal long before the concept of “personalized medicine” became popular. Health professionals have always taken into consideration the individual characteristics of their patients when diagnosing, and treating them. Patients have cared for themselves and for each other, contributed to medical research, and advocated for new treatments. Given this history, why has the notion of personalized medicine gained so much traction at the beginning of the new millennium? Personalized Medicine investigates the recent movement for patients’ involvement in how they are treated, diagnosed, and medicated; a movement that accompanies the increasingly popular idea that people should be proactive, well-informed participants in their own healthcare. While it is often the case that participatory practices in medicine are celebrated as instances of patient empowerment or, alternatively, are dismissed as cases of patient exploitation, Barbara Prainsack challenges these views to illustrate how personalized medicine can give rise to a technology-focused individualism, yet also present new opportunities to strengthen solidarity. Facing the future, this book reveals how medicine informed by digital, quantified, and computable information is already changing the personalization movement, providing a contemporary twist on how medical symptoms or ailments are shared and discussed in society. Bringing together empirical work and critical scholarship from medicine, public health, data governance, bioethics, and digital sociology, Personalized Medicine analyzes the challenges of personalization driven by patient work and data. This compelling volume proposes an understanding that uses novel technological practices to foreground the needs and interests of patients, instead of being ruled by them.

Part of the Oxford Textbooks in Clinical Neurology (OTCN) series, this volume covers the basic science and clinical concepts underlying the movement disorders, as well as the diagnosis and treatment of individual hypokinetic and hyperkinetic movement disorders.

This book is for personalized medicine as a prescription of specific treatments and therapeutics best suited for an individual and considers genetic as well as environmental factors that influence responses to therapy. Best approaches are described for integration of all available technologies for optimizing the therapy of individual patients. This comprehensive third edition covers the latest advances in personalized medicine and several chapters are devoted to various specialties, particulary cancer which is the largest area of application. The book discusses the development of personalized medicine and various players in it such as companies, academic institutions, the government, and the public as the consumer of healthcare. Additionally, the roles of bioinformatics, electronic health records, and digital technologies for personalized medicine are discussed. Textbook of Personalized Medicine, 3rd Edition serves as a convenient source of information for students at many levels and in a wide range of fields, including physicians, scientists, and decision makers in the biopharmaceutical and healthcare industries.