Machine Learning and Artificial Intelligence in Radiation Oncology

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Machine Learning in Radiation Oncology: A Guide for Clinicians is designed for the application of practical concepts in machine learning to clinical radiation oncology. The book addresses the existing void in a resource to educate practicing clinicians on how machine learning can be used to improve clinical and patient-centered outcomes. Sections cover the fundamental concepts of machine learning and radiation oncology, detail techniques applied in genomics, discuss translational opportunities, such as in radiogenomics and autosegmentation, present current clinical applications in clinical decision-making, cover how to integrate AI into workflow and use cases, and elaborate on cross-collaborations within industry. The book is a valuable resource for oncologists, radiologists and members of the biomedical field who want to learn more about machine learning and its present and potential uses in radiation oncology.