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

Written by renowned author Barry S. Rosenstein, this book is a groundbreaking resource designed to bridge the gap between machine learning and clinical radiation oncology. It provides a much-needed guide for practicing clinicians to harness the power of machine learning to improve patient outcomes and revolutionize the field of radiation oncology.

Filling the Knowledge Gap in Machine Learning and Radiation Oncology

The book addresses a significant void in the current literature by educating clinicians on the practical applications of machine learning in radiation oncology. With its unique blend of fundamental concepts, translational opportunities, and current clinical applications, this book is an indispensable resource for oncologists, radiologists, and biomedical professionals seeking to stay at the forefront of this rapidly evolving field.

Structured into Three Comprehensive Sections

The book is divided into three sections, carefully crafted to provide a comprehensive understanding of machine learning and its applications in radiation oncology. The first section delves into the fundamental concepts of machine learning and radiation oncology, exploring techniques applied in genomics. The second section discusses translational opportunities, including radiogenomics and autosegmentation. The final section encompasses current clinical applications in clinical decision making, workflow integration, use cases, and cross-collaborations with industry.

Expert Insights from Diverse Perspectives

This book brings together a diverse group of international experts from academia, research, and industry, providing a balanced and comprehensive view of the complex topic. The contributors include practicing clinicians, research scientists, and AI industry researchers, ensuring a rich mix of new clinical ideas, research findings, and novel theoretical approaches.

With its focus on practical applications, real-world examples, and expert insights, this book is an essential resource for anyone seeking to leverage machine learning and artificial intelligence to improve outcomes in radiation oncology.

Book Details:

• Publisher: Elsevier Science

• Publication Date: December 2, 2023

• Language: English

• ISBN: 9780128220009 (Hardcover), 9780128220016 (eBook)