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Sinopsis
This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
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This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
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Machine Learning in Radiation Oncology
Publicado por
Springer International Publishing Okt 2016, 2016
ISBN 10: 3319354647
ISBN 13: 9783319354644
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities. 352 pp. Englisch. Nº de ref. del artículo: 9783319354644
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Machine Learning in Radiation Oncology
Publicado por
Springer International Publishing, 2016
ISBN 10: 3319354647
ISBN 13: 9783319354644
Nuevo
Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 4 de 5 estrellas
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a complete overview of the role of machine learning in radiation oncology and medical physicsCovers the use of machine learning in quality assurance, computer-aided detection, image-guided radiotherapy, respiratory motion management, and . Nº de ref. del artículo: 458602937
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Machine Learning in Radiation Oncology: Theory and Applications
Librería: Books Puddle, New York, NY, Estados Unidos de America
Calificación del vendedor: 4 de 5 estrellas
Condición: New. pp. 350. Nº de ref. del artículo: 26378362261
Cantidad disponible: 4 disponibles
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Machine Learning in Radiation Oncology | Theory and Applications
Publicado por
Springer Nature Switzerland, 2016
ISBN 10: 3319354647
ISBN 13: 9783319354644
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Taschenbuch
Librería: preigu, Osnabrück, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Machine Learning in Radiation Oncology | Theory and Applications | Issam El Naqa (u. a.) | Taschenbuch | xiv | Englisch | 2016 | Springer Nature Switzerland | EAN 9783319354644 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Nº de ref. del artículo: 111861547
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Machine Learning in Radiation Oncology
Publicado por
Springer International Publishing, Springer Nature Switzerland Okt 2016, 2016
ISBN 10: 3319354647
ISBN 13: 9783319354644
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Neuware -¿This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 352 pp. Englisch. Nº de ref. del artículo: 9783319354644
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Machine Learning in Radiation Oncology : Theory and Applications
Publicado por
Springer International Publishing, 2016
ISBN 10: 3319354647
ISBN 13: 9783319354644
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities. Nº de ref. del artículo: 9783319354644
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EUR 62,99
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Machine Learning in Radiation Oncology: Theory and Applications
Librería: Revaluation Books, Exeter, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: Brand New. reprint edition. 350 pages. 9.25x6.10x0.83 inches. In Stock. Nº de ref. del artículo: 3319354647
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