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Machine Learning in Radiation Oncology false
By:Issam El Naqa,Ruijiang Li,Martin J. Murphy
Published on 2016-10-12 by Springer

\u200bThis 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.

This Book was ranked at 36 by Google Books for keyword Machine Learning.

Book ID of Machine Learning in Radiation Oncology's Books is SUpYvgAACAAJ, Book which was written byIssam El Naqa,Ruijiang Li,Martin J. Murphyhave ETAG "s/qFKCHRjfg"

Book which was published by Springer since 2016-10-12 have ISBNs, ISBN 13 Code is 9783319354644 and ISBN 10 Code is 3319354647

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Book which have "336 Pages" is Printed at BOOK under CategoryMedical

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Machine Learning in Radiation Oncology byIssam El Naqa,Ruijiang Li,Martin J. Murphy

Machine Learning in Radiation Oncology -Issam El Naqa,Ruijiang Li,Martin J. Murphy- 9783319354644

Machine Learning in Radiation Oncology -Issam El Naqa,Ruijiang Li,Martin J. Murphy- 3319354647

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