Preventive Medicine: Artificial Intelligence

Artificial Intelligence, Machine Learning, and Mental Health in Pandemics by Shikha Jain; Kavita Pandey; Princi Jain et al, 2022 Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach provides a comprehensive guide for public health authorities, researchers and health professionals in psychological health. The book takes a unique approach by exploring how Artificial Intelligence (AI) and Machine Learning (ML) based solutions can assist with monitoring, detection and intervention for mental health at an early stage. Chapters include computational approaches, computational models, machine learning based anxiety and depression detection and artificial intelligence detection of mental health. With the increase in number of natural disasters and the ongoing pandemic, people are experiencing uncertainty, leading to fear, anxiety and depression, hence this is a timely resource on the latest updates in the field.

Artificial Intelligence and Precision Oncology by Zodwa Dlamini, 2023 This book highlights the use of artificial intelligence (AI), big data and precision oncology for medical decision making in cancer screening, diagnosis, prognosis and treatment. Precision oncology has long been thought of as ideal for the management and treatment of cancer. This strategy promises to revolutionize the treatment, control, and prevention of cancer by tailoring tests, treatments and predictions to specific individuals or population groups. In order to accomplish these goals, vast amounts of patient or population group specific data needs to be integrated and analysed to be able to identify key patterns or features which can be used to define or characterize the disease or the response to the disease in these individuals. These patterns or features can be as varied as molecular patterns or features in medical images. This level of data analysis and integration can only be achieved through the use of AI. The book is divided into three parts starting with a section on the use of artificial intelligence for screening, diagnosis and monitoring in precision oncology. The second part: Artificial intelligence and Omics in precision oncology, highlights the use of AI and epigenetics, metabolomics, microbiomics in precision oncology. The third part covers artificial intelligence in cancer therapy and its clinical applications. It also highlights the use of AI tools for risk prediction, early detection, diagnosis and accurate prognosis. This book, written by experts in the field from academia and industry, will appeal to cancer researchers, clinical oncologists, pathologists, medical students, academic teaching staff and medical residents interested in cancer research as well as those specialising as clinical oncologists.

Clinical Trials, 2nd ed. by Tom Brody, 2016 Clinical Trials, Second Edition, offers those engaged in clinical trial design a valuable and practical guide. This book takes an integrated approach to incorporate biomedical science, laboratory data of human study, endpoint specification, legal and regulatory aspects and much more with the fundamentals of clinical trial design. It provides an overview of the design options along with the specific details of trial design and offers guidance on how to make appropriate choices. Full of numerous examples and now containing actual decisions from FDA reviewers to better inform trial design, the 2nd edition of Clinical Trials is a must-have resource for early and mid-career researchers and clinicians who design and conduct clinical trials.

Digital Health, AI and Generative AI in Healthcare by Terry Adirim, 2025 The purpose of this title is to provide a comprehensive foundation for all medical professionals and healthcare-professions students in understanding Artificial Intelligence (AI). With the advent of generative AI, including the release of Open AI's ChatGPT in 2022, the world entered a new age of rapid advancements in technology that will significantly change the way clinicians practice medicine, operate healthcare institutions, and conduct research. At the heart of this penetrating book is the idea that medical schools, medical training programs and other health education institutions must undertake a key role in developing AI literacy for clinicians across the spectrum of medical education that includes all health professions. Moreover, assert the authors, AI literacy should be incorporated within medical school curriculums as a core competency, as well as into graduate medical education training programs and continuing medical education courses.This timely and easy-to-read guide offers a wide range of chapters that discuss the core concepts and issues relating to AI in medicine, including a basic understanding of algorithms, machine learning, large language models and natural language processing, the limits and pitfalls of AI, ethical and legal issues, the evolving regulatory landscape around AI, as well as how AI is currently being used in healthcare, to name just several compelling topics. Additionally, AI technologies will change how medical school curriculums are delivered and how student competencies are assessed, maintain the authors. Therefore, medical educators will not only need to rethink how and what medical information is conveyed to students during formal instruction, but also must be prepared for AI-powered programs being used to assess students and trainees for the purpose of licensure and board certification. A timely and soon-to-be gold standard resource in the field, Digital Health, AI, and Generative AI: A Concise, Practical Guide for Clinicians will be of great interest to medical professionals, trainees, administrators, policymakers, and anyone interested in the fast-evolving intersection of digital technologies and healthcare.

Digital Therapeutics for Mental Health and Addiction by Nicholas C. Jacobson; Tobias Kowatsch; Lisa A. Marsch, 2022 Digital Therapeutics for Mental Health and Addiction: The State of the Science and Vision for the Future presents the foundations of digital therapeutics with a broad audience in mind, ranging from bioengineers and computer scientists to those in psychology, psychiatry and social work. Sections cover cutting-edge advancements in the field, offering advice on how to successfully implement digital therapeutics. Readers will find sections on evidence for direct-to-consumer standalone digital therapeutics, the efficacy of integrating digital treatments within traditional healthcare settings, and recent innovations currently transforming the field of digital therapeutics towards experiences which are more personalized, adaptable and engaging. This book gives a view on current limitations of the technology, ideas for problem-solving the challenges of designing this technology, and a perspective on future research directions. For all readers, the content on cultural, legal and ethical dimensions of digital mental health will be useful.

Healthcare in the Digital Age by Marta. Bertolaso; Maria Laura Ilardo; Jaume Ribera, 2025 This book offers a comprehensive exploration of the dynamic relationship between digital technology and healthcare delivery, emphasising sustainable innovation in health services. It explores how digital technologies improve healthcare outcomes, enhance patient and community experiences, and streamline healthcare management, while addressing ethical, philosophical, and policy challenges tied to healthcare digitization. Examining trends such as telemedicine, AI diagnostics, data security, and the Internet of Medical Things (IoMT), the book highlights global case studies, lessons learned, and strategies for integrating these technologies sustainably. It discusses the contextual, economic, and social impacts of digital health, presenting frameworks for their evaluation and improvement. Advocating for regulatory policies that prioritise privacy, accessibility and enhance responsible initiative, the book calls for collaborative approaches. Aimed at healthcare professionals, policymakers, and academics, this resource provides insights into creating a more efficient and equitable healthcare system, aligning with the broader goals of public health and social justice.

Precision Medicine and Artificial Intelligence: the Perfect Fit for Autoimmunity by Michael Mahler, 2021 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.

Sex and Gender Bias in Technology and Artificial Intelligence by Davide Cirillo; Silvina Catuara Solarz; Emre Guney, 2022 Sex and Gender Bias in Technology and Artificial Intelligence: Biomedicine and Healthcare Applications details the integration of sex and gender as critical factors in innovative technologies (artificial intelligence, digital medicine, natural language processing, robotics) for biomedicine and healthcare applications. By systematically reviewing existing scientific literature, a multidisciplinary group of international experts analyze diverse aspects of the complex relationship between sex and gender, health and technology, providing a perspective overview of the pressing need of an ethically-informed science. The reader is guided through the latest implementations and insights in technological areas of accelerated growth, putting forward the neglected and overlooked aspects of sex and gender in biomedical research and healthcare solutions that leverage artificial intelligence, biosensors, and personalized medicine approaches to predict and prevent disease outcomes. The reader comes away with a critical understanding of this fundamental issue for the sake of better future technologies and more effective clinical approaches.

Surveillance, Prevention, and Control of Infectious Diseases : An AI Perspective by Muhammad E. H. Chowdhury; Serkan Kiranyaz, 2024 This is a pioneering book that delves into the intersection of artificial intelligence (AI) and healthcare, specifically focusing on the detection and prevention of infectious diseases. Authored by leading experts in the field, this book offers a comprehensive overview of the latest advancements, challenges, and applications of AI in combating infectious diseases. With a unique emphasis on big data, wearable data, and computer vision, the book presents original research works that showcase innovative approaches to leveraging AI for disease surveillance, screening, and severity stratification. Through a combination of review chapters summarizing the current state of the field and novel applications of AI technology, readers gain valuable insights into the potential of AI in addressing major life-threatening infectious diseases identified by the UN Sustainable Development Goal 3. The book's structure ensures a balanced blend of theoretical foundations and practical applications, making it accessible to both researchers and healthcare professionals. By exploring cutting-edge methodologies and case studies, the book equips readers with the knowledge and tools needed to harness the power of AI in the fight against infectious diseases, ultimately contributing to global efforts to improve public health outcomes. With its interdisciplinary approach and focus on AI-driven solutions, " Surveillance, prevention, and control of infectious diseases: An AI perspective" serves as an invaluable resource for researchers, practitioners, and policymakers seeking to stay abreast of the latest developments in this rapidly evolving field. Whether exploring the role of wearable devices in disease monitoring or examining the potential of computer vision for early detection, this book offers a comprehensive overview of AI applications that have the potential to revolutionize infectious disease management and prevention strategies.