Machine and Deep Learning in Oncology, Medical Physics and Radiology
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Beschreibung
This book, now in an extensively revised and updated second edition, provides a comprehensive overview of both machine learning and deep learning and their role in oncology, medical physics, and radiology. Readers will find thorough coverage of basic theory, methods, and demonstrative applications in these fields. An introductory section explains machine and deep learning, reviews learning methods, discusses performance evaluation, and examines software tools and data protection. Detailed individual sections are then devoted to the use of machine and deep learning for medical image analysis, treatment planning and delivery, and outcomes modeling and decision support. Resources for varying applications are provided in each chapter, and software code is embedded as appropriate for illustrative purposes. The book will be invaluable for students and residents in medical physics, radiology, and oncology and will also appeal to more experienced practitioners and researchers and members ofapplied machine learning communities.
This book, now in an extensively revised and updated second edition, provides a comprehensive overview of both machine learning and deep learning and their role in oncology, medical physics, and radiology. Readers will find thorough coverage of basic theory, methods, and demonstrative applications in these fields. An introductory section explains machine and deep learning, reviews learning methods, discusses performance evaluation, and examines software tools and data protection. Detailed individual sections are then devoted to the use of machine and deep learning for medical image analysis, treatment planning and delivery, and outcomes modeling and decision support. Resources for varying applications are provided in each chapter, and software code is embedded as appropriate for illustrative purposes. The book will be invaluable for students and residents in medical physics, radiology, and oncology and will also appeal to more experienced practitioners and researchers and members ofapplied machine learning communities.
Reference text for machine and deep learning in oncology, medical physics, and radiology From theory to practice with examples Provides a complete overview of the role of machine learning in radiation oncology and medical physics
Autor*in
Issam El Naqa
Themen in »Machine and Deep Learning in Oncology, Medical Physics and Radiology«
Machine Learning Deep Learning Artificial Intelligence Medical Physics Image Analysis Decision Support Outcome Modelling Radiation Physics Treatment Planning Radiation Oncology Oncology Radiology
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“This is a must-read for anyone interested in the intersection of technology and healthcare. A roadmap, if you like, to a future where cancer can be conquered with the help of AI and human ingenuity.” (Dewinder Bhachu, RAD Magazine, June, 2024)
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