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

Machine Learning and Artificial Intelligence in Radiation Oncology provides practical concepts for clinical radiation oncology, covering fundamental concepts, translational opportunities, and clinical applications, making it a valuable resource for oncologists, radiologists, and biomedical field members.

Format: Paperback / softback
Length: 300 pages
Publication date: 01 December 2023
Publisher: Elsevier Science Publishing Co Inc

Machine Learning and Artificial Intelligence in Radiation Oncology: A Guide for Clinicians is a comprehensive resource that aims to equip practicing clinicians with practical knowledge and skills in applying machine learning to clinical radiation oncology. The book addresses the gap in existing resources by providing a comprehensive overview of machine learning concepts and their applications in clinical radiation oncology. It is divided into three sections: Fundamentals of Machine Learning and Radiation Oncology, Translational Opportunities, and Current Clinical Applications. The first section covers fundamental concepts of machine learning, including techniques applied in genomics, and provides a foundation for understanding how machine learning can be used to improve clinical and patient-centered outcomes. The second section explores translational opportunities, such as radiogenomics and autosegmentation, and highlights how machine learning can be used to enhance the understanding of disease and improve patient care. The final section focuses on current clinical applications of machine learning in clinical decision making, workflow integration, use cases, and cross-collaborations with industry. The book is a valuable resource for oncologists, radiologists, and other members of the biomedical field who are interested in learning more about machine learning as a support for radiation oncology. It provides a clear and concise explanation of machine learning concepts and their applications, and includes numerous examples and case studies to illustrate their practical relevance. Additionally, the book includes a comprehensive list of references and resources for further reading, making it a valuable resource for both beginners and experienced practitioners.

Dimension: 234 x 191 (mm)
ISBN-13: 9780128220009