Department of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan.
Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Adv Exp Med Biol. 2024;1462:307-322. doi: 10.1007/978-3-031-64892-2_18.
The chapter explores the extensive integration of artificial intelligence (AI) in healthcare systems, with a specific focus on its application in stereotactic radiosurgery. The rapid evolution of AI technology has led to promising developments in this field, particularly through the utilization of machine learning and deep learning models. The diverse implementation of AI algorithms was developed from various aspects of radiosurgery, including the successful detection of spontaneous tumors and the automated delineation or segmentation of lesions. These applications show potential for extension to longitudinal treatment follow-up. Additionally, the chapter highlights the established use of machine learning algorithms, particularly those incorporating radiomic-based analysis, in predicting treatment outcomes. The discussion encompasses current achievements, existing limitations, and the need for further investigation in the dynamic intersection of AI and radiosurgery.
本章探讨了人工智能(AI)在医疗保健系统中的广泛融合,特别关注其在立体定向放射外科中的应用。人工智能技术的快速发展带来了该领域的有前景的进展,特别是通过利用机器学习和深度学习模型。从放射外科的各个方面开发了各种 AI 算法的实施,包括成功检测自发性肿瘤和自动描绘或分割病变。这些应用显示出在纵向治疗随访中扩展的潜力。此外,本章强调了机器学习算法的既定用途,特别是那些纳入基于放射组学分析的算法,用于预测治疗结果。讨论包括当前的成就、现有局限性以及在 AI 和放射外科的动态交叉点进一步研究的必要性。
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