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Machine Learning and Artificial Intelligence in Radiation Oncology: A Guide for Clinicians
Rosenstein Barry S.,Rattay Tim,Kang John (Author)
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Academic Press
· Nuevo
Machine Learning and Artificial Intelligence in Radiation Oncology: A Guide for Clinicians - Rosenstein Barry S.,Rattay Tim,Kang John
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Synopsis "Machine Learning and Artificial Intelligence in Radiation Oncology: A Guide for Clinicians"
Machine Learning and Artificial Intelligence in Radiation Oncology: A Guide for Clinicians is designed for the application of practical concepts in machine learning to clinical radiation oncology. It addresses the existing void in a resource to educate practicing clinicians about how machine learning can be used to improve clinical and patient-centered outcomes. This book is divided into three sections: the first addresses fundamental concepts of machine learning and radiation oncology, detailing techniques applied in genomics; the second section discusses translational opportunities, such as in radiogenomics and autosegmentation; and the final section encompasses current clinical applications in clinical decision making, how to integrate AI into workflow, use cases, and cross-collaborations with industry. The book is a valuable resource for oncologists, radiologists and several members of biomedical field who need to learn more about machine learning as a support for radiation oncology.
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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Nuevo.
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