Zhu Simeng, Ma Sung Jun, Farag Alexander, Huerta Timothy, Gamez Mauricio E, Blakaj Dukagjin M
Department 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.
Department 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; Department of Otolaryngology-Head and Neck Surgery, Jacksonville Sinus and Nasal Institute, 836 Prudential Drive Suite 1601, Jacksonville, FL 32207, USA.
Hematol Oncol Clin North Am. 2025 Apr;39(2):453-469. doi: 10.1016/j.hoc.2024.12.002. Epub 2025 Jan 7.
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.
本综述探讨了人工智能和机器学习（AI/ML）在放射肿瘤学中的应用，重点关注计算机视觉（CV）和自然语言处理（NLP）技术。我们研究了数字病理学和放射组学中基于CV的AI/ML，强调了展示其效用的前瞻性临床研究。我们还回顾了基于NLP的AI/ML在临床文档分析、知识评估和质量保证方面的应用。在认识到临床应用所面临挑战的同时，本综述强调了AI/ML在提高放射肿瘤学护理的精准性、效率和质量方面的变革潜力。
