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 l...

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Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Kang, John (Editor), Rattay, Tim (Editor), Rosenstein, Barry S. (Editor)
Format: eBook
Language:English
Published: London, United Kingdom ; San Diego, CA : Academic Press, [2024]
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:"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."--Provided by publisher.
Physical Description:1 online resource : illustrations
Bibliography:Includes bibliographical references and index.
ISBN:0128220015
9780128220016