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Artificial Intelligence, Machine Learning and Big Data in Radiation Oncology
Simeng Zhu1, Sung Jun Ma1, Alexander Farag2
1Department of Radiation Oncology, The Arthur G. James Cancer Hospital and Richard J. Solove Research Institute, The Ohio State University Comprehensive Cancer Center, 460 West 10th Avenue, Columbus, OH 43210, USA.
None:
This review explores the applications of artificial intelligence and machine learning (AI/ML) in radiation oncology, focusing on computer vision (CV) and natural language processing (NLP) techniques. We examined CV-based AI/ML in digital pathology and radiomics, highlighting the prospective clinical studies demonstrating their utility. We also reviewed NLP-based AI/ML applications in clinical documentation analysis, knowledge assessment, and quality assurance. While acknowledging the challenges for clinical adoption, this review underscores the transformative potential of AI/ML in enhancing precision, efficiency, and quality of care in radiation oncology.
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