The clinical use of Artificial Intelligence (AI) in radiation
oncology is in its infancy. However, it is certain that AI is
capable of making radiation oncology more precise and personalized
with improved outcomes. Radiation oncology deploys an array of
state-of-the-art technologies for imaging, treatment, planning,
simulation, targeting, and quality assurance while managing the
massive amount of data involving therapists, dosimetrists,
physicists, nurses, technologists, and managers. AI consists of
many powerful tools which can process a huge amount of
inter-related data to improve accuracy, productivity, and
automation in complex operations such as radiation oncology.This
book offers an array of AI scientific concepts, and AI technology
tools with selected examples of current applications to serve as a
one-stop AI resource for the radiation oncology community. The
clinical adoption, beyond research, will require ethical
considerations and a framework for an overall assessment of AI as a
set of powerful tools.30 renowned experts contributed to sixteen
chapters organized into six sections: Define the Future, Strategy,
AI Tools, AI Applications, and Assessment and Outcomes. The future
is defined from a clinical and a technical perspective and the
strategy discusses lessons learned from radiology experience in AI
and the role of open access data to enhance the performance of AI
tools. The AI tools include radiomics, segmentation, knowledge
representation, and natural language processing. The AI
applications discuss knowledge-based treatment planning and
automation, AI-based treatment planning, prediction of radiotherapy
toxicity, radiomics in cancer prognostication and treatment
response, and the use of AI for mitigation of error propagation.
The sixth section elucidates two critical issues in the clinical
adoption: ethical issues and the evaluation of AI as a
transformative technology.
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