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Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. - Summarizes AI advances for use in mental health practice - Includes advances in AI based decision-making and consultation - Describes AI applications for assessment and treatment - Details AI advances in robots for clinical settings - Provides empirical data on clinical efficacy - Explores practical issues of use in clinical settings
In mental health care, artificial intelligence (AI) tools can enhance diagnostic accuracy, personalize treatment plans, and provide support through virtual therapy and chatbots that offer real-time assistance. These technologies can help identify early signs of mental health issues by analyzing patterns in speech, behavior, and physiological data. However, the integration of AI also raises concerns about privacy, data security, and the potential for algorithmic bias, which could impact quality of care. As AI continues to evolve, its role in psychological well-being and healthcare will depend on addressing these ethical and practical considerations while harnessing its potential to improve mental health outcomes and streamline healthcare delivery. AI Technologies and Advancements for Psychological Well-Being and Healthcare discusses the latest innovations in AI that are transforming the landscape of mental health and healthcare services. This book explores how AI applications, such as machine learning algorithms and natural language processing, are enhancing diagnostic accuracy, personalizing treatment options, and improving patient outcomes. Covering topics such as behavioral artificial intelligence, medical diagnosis, and precision medicine, this book is an excellent resource for mental health professionals, healthcare providers and administrators, AI and data scientists, academicians, researchers, healthcare policymakers, and more.
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
In mental health care, artificial intelligence (AI) tools can enhance diagnostic accuracy, personalize treatment plans, and provide support through virtual therapy and chatbots that offer real-time assistance. These technologies can help identify early signs of mental health issues by analyzing patterns in speech, behavior, and physiological data. However, the integration of AI also raises concerns about privacy, data security, and the potential for algorithmic bias, which could impact quality of care. As AI continues to evolve, its role in psychological well-being and healthcare will depend on addressing these ethical and practical considerations while harnessing its potential to improve mental health outcomes and streamline healthcare delivery. AI Technologies and Advancements for Psychological Well-Being and Healthcare discusses the latest innovations in AI that are transforming the landscape of mental health and healthcare services. This book explores how AI applications, such as machine learning algorithms and natural language processing, are enhancing diagnostic accuracy, personalizing treatment options, and improving patient outcomes. Covering topics such as behavioral artificial intelligence, medical diagnosis, and precision medicine, this book is an excellent resource for mental health professionals, healthcare providers and administrators, AI and data scientists, academicians, researchers, healthcare policymakers, and more.
In the ancient world, health seekers traversed vast distances to pursue well-being. Fast forward to the 21st century, and the concept of medical tourism has evolved into a global industry worth billions of dollars. The burgeoning demand for quality healthcare has pushed traditional boundaries, necessitating a more sophisticated and interconnected healthcare ecosystem. Integrating Artificial Intelligence (AI) into medical practices empowers individuals to actively manage their health while providing healthcare practitioners with invaluable insights for tailored patient care. Impact of AI and Robotics on the Medical Tourism Industry delves into the transformative impact of AI and robotics on this dynamic sector. It explores how AI can encourage and assist patients in their health plans while augmenting healthcare practitioners' capabilities to utilize specific patient data to offer unique guidance. It dissects real-world examples, such as Cleveland Clinic Abu Dhabi's integration of robotic surgery, showcasing how these technologies revolutionize traditional medical practices.
Within the context of Industrial 4.0 and beyond, developing and managing the technologies and operations key to sustaining the success of manufacturing businesses is crucial, and the promotion of manufacturing-engineering education, training, and research is of vital importance. This book presents the proceedings of ICMR 2022, the 19th International Conference in Manufacturing Research, Incorporating the 36th National Conference in Manufacturing Research, held in Derby, UK, from 6 - 8 September 2022. For over two decades, ICMR has been the main manufacturing research conference held in the UK. Bringing together researchers, academics, and industrialists to share their knowledge and experience, the conference provides a friendly and inclusive platform for a broad community of researchers who share the common goal of making digital and advanced manufacturing as efficient and effective as possible. The theme of ICMR2022 is smart manufacturing. Of the 78 papers submitted, 58 were accepted for presentation after review and are included here. This represents an acceptance rate of 72%. The book is divided into 8 sections: smart manufacturing; digital manufacturing; additive manufacturing; robotics and industrial automation; composite manufacturing and machining processes; product design, development and quality management; information and knowledge management; and decision support and production optimization. Exploring all core areas of digital and advanced manufacturing engineering, the book will be of interest to all those working in the field.
This book constitutes the refereed proceedings of the 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, held in Costa de Caparica, Portugal, in July 2021.* The 34 papers presented were carefully reviewed and selected from 92 submissions. The papers present selected results produced in engineering doctoral programs and focus on technological innovation for industry and service systems. Research results and ongoing work are presented, illustrated and discussed in the following areas: collaborative networks; smart manufacturing; cyber-physical systems and digital twins; intelligent decision making; smart energy management; communications and electronics; classification systems; smart healthcare systems; and medical devices. *The conference was held virtually. Chapters “Characteristics of Adaptable Control of Production Systems and the Role of Self-organization Towards Smart Manufacturing” and “Predictive Manufacturing: Enabling Technologies, Frameworks and Applications” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
In recent times, research in human-focused robot technologies aims to bring social-emotional intelligence closer, which interconnects with human lifestyles. Among several areas that can benefit from it, the healthcare sector, which consists of many possible areas of therapeutic interposition, is the most vital. Further, there is always concern about patient adherence to cardiac rehabilitation. It is essential to understand the motivational factors affecting patient participation and compliance with cardiac rehabilitation by recognizing and understanding the nature of patient experiences. Cognitive Cardiac Rehabilitation Using IoT and AI Tools describes the application of AI techniques used to extract features from brain and heart signal data and to better efficiency compared to the existing methods. This book also describes the application of AI tools to classify disorders and better performance compared to the existing benchmarks. Covering topics such as cardiac rehabilitation, heart disease prediction, and online social media analytics, this premier reference source is an excellent resource for healthcare professionals, medical engineers, hospital administrators, students and educators of higher education, researchers, and academicians.
Much remains to be known about public utilities system organization, efficiency, management, legislation, practices, and solutions worldwide, as well as the implications for sustainable development in different countries. Thus, a better understanding of the different management practices in public utilities across different contexts is needed to assess their impact on efficiency and sustainability, especially in the changed climate conditions. Transformation and Efficiency Enhancement of Public Utilities Systems: Multidimensional Aspects and Perspectives considers the necessity to transform public utilities systems towards sustainability and efficiency. This publication investigates the performance management process of public utility systems and evaluates the efficiency of public utilities to propose potential improvements. The book encourages amenable authorities to create more efficient and effective management systems and improve their performance. Additionally, it provides the government with a systemic approach to public utilities system transformation and development. Covering key topics such as public hygiene, sustainability, and environmental protection, this premier reference source is ideal for government officials, policymakers, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.
There are more than 80 different sleep disorders including insomnia, sleep apnea, restless leg syndrome, hypersomnia, circadian rhythm disorders, and parasomnia. Good sleep is necessary for optimal health and can affect hormone levels and weight. The use of artificial intelligence (AI) and biomedical signals and images can help in healthcare diagnostics that are related to these and other sleep disorders. Advancing the Investigation and Treatment of Sleep Disorders Using AI presents an overview of sleep disorders based on machine intelligence methods in order to learn and explore the latest advancements, developments, methods, systems, futuristic approaches, and algorithms towards sleep disorders and to address their challenges. This book also discusses recent and future advancements in various feature extraction techniques and machine learning methods. Covering topics such as biomedical signal processing, augmented reality for clinical investigation, and sleep disorder detection, this book is essential for sleep medicine practitioners, clinical psychologists, psychiatrists, medical technologists, doctors, IT specialists, biomedical engineers, researchers, graduate students, and academicians.