Machine Learning in Radiation Oncology: Theory and Applications

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Machine Learning in Radiation Oncology: Theory and Applications - El Naqa, Issam (Editor), and Li, Ruijiang (Editor), and Murphy, Martin J (Editor)
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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 ...

Machine Learning in Radiation Oncology: Theory and Applications 2016, Springer

ISBN-13: 9783319354644

Trade paperback

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Machine Learning in Radiation Oncology: Theory and Applications 2015, Springer, Cham

ISBN-13: 9783319183046

2015 edition

Hardcover

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