计算机工程与应用 ›› 2023, Vol. 59 ›› Issue (10): 35-47.DOI: 10.3778/j.issn.1002-8331.2207-0062
张汉明,马金刚,张宁宁,赵珍珍,李明
出版日期:
2023-05-15
发布日期:
2023-05-15
ZHANG Hanming, MA Jingang, ZHANG Ningning, ZHAO Zhenzhen, LI Ming
Online:
2023-05-15
Published:
2023-05-15
摘要: 随着癫痫患者数量的逐年增加,及时准确地检测出癫痫疾病具有重要的现实意义。如今深度学习发展迅速,被广泛用于医疗领域,基于深度学习的癫痫检测任务也成为目前的研究热点。通过梳理近几年的相关文献后,对深度学习在癫痫检测中的算法应用进行了系统概述。介绍了癫痫的发病原理、病因和治疗方法等;讲解了癫痫检测时所使用的脑电图和癫痫发作的整体过程划分;简单对比了传统机器学习和深度学习在此领域应用的不同之处;重点综述了利用深度学习检测癫痫各阶段脑电信号的研究进展,包括癫痫双阶段、三阶段和多阶段的脑电检测,并对癫痫各阶段的检测算法进行了比较;最后对该领域的研究现状和未来发展方向进行了总结和展望。
张汉明, 马金刚, 张宁宁, 赵珍珍, 李明. 深度学习在癫痫检测中的应用进展[J]. 计算机工程与应用, 2023, 59(10): 35-47.
ZHANG Hanming, MA Jingang, ZHANG Ningning, ZHAO Zhenzhen, LI Ming. Application Progress of Deep Learning in Epilepsy Detection[J]. Computer Engineering and Applications, 2023, 59(10): 35-47.
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