Li Xiangyu, Xiang Sishi, Li Guilin
Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
Interv Neuroradiol. 2024 Mar 22:15910199241238798. doi: 10.1177/15910199241238798.
BACKGROUND: Artificial intelligence (AI) has rapidly advanced in the medical field, leveraging its intelligence and automation for the management of various diseases. Brain arteriovenous malformations (AVM) are particularly noteworthy, experiencing rapid development in recent years and yielding remarkable results. This paper aims to summarize the applications of AI in the management of AVMs management. METHODS: Literatures published in PubMed during 1999-2022, discussing AI application in AVMs management were reviewed. RESULTS: AI algorithms have been applied in various aspects of AVM management, particularly in machine learning and deep learning models. Automatic lesion segmentation or delineation is a promising application that can be further developed and verified. Prognosis prediction using machine learning algorithms with radiomic-based analysis is another meaningful application. CONCLUSIONS: AI has been widely used in AVMs management. This article summarizes the current research progress, limitations and future research directions.
背景:人工智能(AI)在医学领域迅速发展,利用其智能和自动化来管理各种疾病。脑动静脉畸形(AVM)尤其值得关注,近年来发展迅速并取得了显著成果。本文旨在总结人工智能在AVM管理中的应用。 方法:回顾了1999年至2022年期间发表在PubMed上讨论人工智能在AVM管理中应用的文献。 结果:人工智能算法已应用于AVM管理的各个方面,特别是在机器学习和深度学习模型中。自动病变分割或勾勒是一个有前景的应用,可以进一步开发和验证。使用基于放射组学分析的机器学习算法进行预后预测是另一个有意义的应用。 结论:人工智能已广泛应用于AVM管理。本文总结了当前的研究进展、局限性和未来的研究方向。
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