Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Machine Learning and Artificial Intelligence in Radiation Oncology: A Guide for Clinicians

Machine Learning and Artificial Intelligence in Radiation Oncology: A Guide for Clinicians

Rattay, Tim
Kang, John
Rosenstein, Barry S.

Paperback

Biology

ISBN10: 0128220007
ISBN13: 9780128220009
Publisher: Academic Press
Published: Dec 4 2023
Pages: 478
Weight: 1.80
Height: 0.97 Width: 7.50 Depth: 9.25
Language: English
**Selected for 2025 Doody's Core Titles(R) in Radiation Oncology**

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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