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Explainable Artificial Intelligence in Medical Imaging: Fundamentals and Applications.

Explainable Artificial Intelligence in Medical Imaging: Fundamentals and Applications.

・ISBN 978-1-032-62633-8 paper GB£ 90.99

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お気に入り
電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 978-1-032-62634-5
著者・編者Khan, Amjad Rehman / Saba, Tanzila (eds.),
シリーズ (Advances in Computational Collective Intelligence)
出版社 (Auerbach, UK)
出版年月2025
ページ数250 pp.
言語ENG
ニュース番号<A03-60768>

解説

Artificial intelligence (AI) in medicine is rising, and it holds tremendous potential for more accurate findings and novel solutions to complicated medical issues. Biomedical AI has potential, especially in the context of precision medicine, in the healthcare industry's next phase of development and advancement. Integration of AI research into precision medicine is the future; however, the human component must always be considered.

Explainable Artificial Intelligence in Medical Imaging: Fundamentals and Applications focuses on the most recent developments in applying artificial intelligence and data science to health care and medical imaging. Explainable artificial intelligence is a well-structured, adaptable technology that generates impartial, optimistic results. New healthcare applications for explicable artificial intelligence include clinical trial matching, continuous healthcare monitoring, probabilistic evolutions, and evidence-based mechanisms. This book overviews the principles, methods, issues, challenges, opportunities, and the most recent research findings. It makes the emerging topics of digital health and explainable AI in health care and medical imaging accessible to a wide audience by presenting various practical applications.

Presenting a thorough review of state-of-the-art techniques for precise analysis and diagnosis, the book emphasizes explainable artificial intelligence and its applications in healthcare. The book also discusses computational vision processing methods that manage complicated data, including physiological data, electronic medical records, and medical imaging data, enabling early prediction. Researchers, academics, business professionals, health practitioners, and students all can benefit from this book's insights and coverage.