Artificial Intelligence Based Primary Care

"Artificial Intelligence based Primary Care: Artificial Intelligence and Human Cognition in General Practice and Family Medicine" gives insight into the concepts and applications of artificial intelligence in primary care that is designed for general practice and family medicine clinicians. With a strong focus on the clinical aspects of artificial intelligence in primary care the reader is enabled to understand different potential use cases of AI within their practice, how to appraise these technologies and how to apply AI applications to real-world clinical scenarios. In 5 sections and 20 chapters, "Artificial Intelligence based Primary Care: Artificial Intelligence and Human Cognition in General Practice and Family Medicine" introduces Artificial intelligence in Primary care, it describes the applications of artificial intelligence, the implementation challenges and concludes with major takeaways and the future of artificial intelligence in primary care. In a special chapter, a day in the life of a General Practitioner is described. An extra compendium provides a recommended list of the Top 100 articles and best books on Artificial Intelligence. This book narrows the knowledge and expertise chasm between the data scientists and primary care clinicians and is a valuable resource for academics and researchers in artificial intelligence, primary care, family medicine, and all those who wish to broaden their knowledge in the allied field.

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

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

In today’s modernized world, the field of healthcare has seen significant practical innovations with the implementation of computational intelligence approaches and soft computing methods. These two concepts present various solutions to complex scientific problems and imperfect data issues. This has made both very popular in the medical profession. There are still various areas to be studied and improved by these two schemes as healthcare practices continue to develop. Computational Intelligence and Soft Computing Applications in Healthcare Management Science is an essential reference source that discusses the implementation of soft computing techniques and computational methods in the various components of healthcare, telemedicine, and public health. Featuring research on topics such as analytical modeling, neural networks, and fuzzy logic, this book is ideally designed for software engineers, information scientists, medical professionals, researchers, developers, educators, academicians, and students.

Foundational Handbook of Artificial Intelligence in Healthcare and Bioscience: A User Friendly Guide for IT Professionals, Healthcare Providers, Researchers, and Clinicians uses color-coded illustrations to explain AI from its basics to modern technologies. Other sections cover extensive, current literature research and citations regarding AI’s role in the business and clinical aspects of health care. The book provides readers with a unique opportunity to appreciate AI technology in practical terms, understand its applications, and realize its profound influence on the clinical and business aspects of health care. Artificial Intelligence is a disruptive technology that is having a profound and growing influence on the business of health care as well as medical diagnosis, treatment, research and clinical delivery. The AI relationships in health care are complex, but understandable, especially when discussed and developed from their foundational elements through to their practical applications in health care. Provides an illustrated, foundational guide and comprehensive descriptions of what Artificial Intelligence is and how it functions Integrates a comprehensive discussion of AI applications in the business of health care Presents in-depth clinical and AI-related discussions on diagnostic medicine, therapeutic medicine, and prevalent disease categories with an emphasis on immunology and genetics, the two categories most influenced by AI Includes comprehensive coverage of a variety of AI treatment applications, including medical/pharmaceutical care, nursing care, stem cell therapies, robotics, and 10 common disease categories with AI applications

This comprehensive work provides a lucid examination of the difficult problems that arise with the implementation of effective primary care. The book has four purposes: to help practitioners of primary care understand what they do and why; to provide a basis for the training of primary care practitioners; to stimulate research that will provide a more substantive basis for improvements in primary care; and to help policy makers understand the difficulties and challenges of primary care and its importance. In addition to discussing systems of primary care and alternative ways of evaluating them, the author addresses important issues such as practitioner-patient communication, information systems and medical records, referral processes, personnel, managed care, financing, quality assessment and community orientation. This unique volume provides a clear and valuable assessment of the basic concepts, issues and challenges in this increasingly important field.

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

Doctors Pierre Pluye and Roland Grad, internationally recognized experts in the fields of knowledge translation and health information studies, along with bestselling author and journalist Julie Barlow, take readers behind the scenes to show how online information is affecting self-care and primary health care in medicine, nursing, and pharmacy. Based on fifteen years of in-depth interviews and research, Look It Up provides essential tips for patients and clinicians to administer and receive the best possible primary health care, while avoiding the perils of unguided self-diagnosis. This book shows how, by dint of an inquiring mind and a smartphone, rapid and accurate acquisition of knowledge keeps primary care clinicians up to date. It also shows how people can determine whether a test is more beneficial than harmful, and how information helps resolve disagreements and improve collaboration with patients and families, and among doctors, pharmacists, and nurses. In the age of easily accessible online information, clinicians have to think differently about how they work. Organized around numerous real clinical stories, Look It Up is an illuminating and lively guide to improving patient care.