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人工智能辅助脑电图在癫痫管理中的进展与挑战

Advancements and Challenges of Artificial Intelligence-Assisted Electroencephalography in Epilepsy Management.

作者信息

Chen Yujie, Ou Zhujing, Zhou Dong, Wu Xintong

机构信息

Department of Neurology, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China.

出版信息

J Clin Med. 2025 Jun 16;14(12):4270. doi: 10.3390/jcm14124270.

Abstract

Artificial intelligence (AI) has emerged as a transformative tool in the analysis and management of epilepsy through its integration with electroencephalography (EEG) data. The adoption of AI-assisted solutions in managing epilepsy holds the potential to significantly enhance the efficiency and accuracy for diagnosing this complex condition. However, AI-assisted EEG technologies are infrequently adopted in clinical settings. In this Review, we provide an overview of AI applications in seizure prediction, detection, syndrome classification, surgical planning, and prognosis prediction. Additionally, we explore the methodological considerations and challenges that are relevant in clinical settings. Overall, AI has the potential to revolutionize epilepsy management, ultimately improving patient outcomes and advancing the field of precision medicine. Fostering interdisciplinary collaborations between AI researchers, neurologists, and ethicists will be crucial in creating integrated solutions that address both technical and clinical requirements.

摘要

人工智能(AI)通过与脑电图(EEG)数据相结合,已成为癫痫分析和管理中的一种变革性工具。在癫痫管理中采用人工智能辅助解决方案有可能显著提高诊断这种复杂病症的效率和准确性。然而,人工智能辅助脑电图技术在临床环境中的应用并不常见。在本综述中,我们概述了人工智能在癫痫发作预测、检测、综合征分类、手术规划和预后预测方面的应用。此外,我们探讨了临床环境中相关的方法学考量和挑战。总体而言,人工智能有潜力彻底改变癫痫管理,最终改善患者预后并推动精准医学领域的发展。促进人工智能研究人员、神经科医生和伦理学家之间的跨学科合作对于创建满足技术和临床需求的综合解决方案至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ab5/12194755/8f0df450ff7a/jcm-14-04270-g001.jpg

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