Machine learning applications in epilepsy.
Machine learning applications in epilepsy.
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机器学习利用统计和计算机科学原理来开发能够通过解释数据而不是通过显式指令来提高性能的算法。除了在图像识别、语言处理和数据挖掘中的广泛应用之外，机器学习技术在从自动成像分析到疾病预测等医学应用中也受到越来越多的关注。这篇综述探讨了癫痫领域的并行进展，重点介绍了脑电图、视频和动力学数据自动癫痫发作检测、自动成像分析和术前计划、药物反应预测以及使用各种数据源预测医疗和手术结果的应用。还简要概述了常用的机器学习方法，以及机器学习技术在癫痫中进一步应用的挑战。随着计算能力的提高、有效机器学习算法的可用性以及更大数据集的积累，临床医生和研究人员将越来越多地受益于对这些技术的熟悉及其在癫痫应用中已经取得的重大进展。
Machine learning leverages statistical and computer science principles to develop algorithms capable of improving their performance through interpretation of data rather than through explicit instructions. Alongside widespread use in image recognition, language processing, and data mining, machine learning techniques have received increasing attention in medical applications, ranging from automated imaging analysis to disease forecasting. This review examines the parallel progress made in epilepsy, highlighting applications in automated seizure detection from EEG, video, and kinetic data, automated imaging analysis and pre-surgical planning, prediction of medication response, and prediction of medical and surgical outcomes using a wide variety of data sources. A brief overview of commonly used machine learning approaches, as well as challenges in further application of machine learning techniques in epilepsy, is also presented. With increasing computational capabilities, availability of effective machine learning algorithms, and accumulation of larger datasets, clinicians and researchers will increasingly benefit from familiarity with these techniques and the significant progress already made in their application in epilepsy.
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影响因子：
3
作者：
Combrisson, Etienne;Jerbi, Karim
通讯作者：
Jerbi, Karim
影响因子：
3.7
作者：
Armañanzas R;Alonso-Nanclares L;Defelipe-Oroquieta J;Kastanauskaite A;de Sola RG;Defelipe J;Bielza C;Larrañaga P
通讯作者：
Larrañaga P
影响因子：
64.8
作者：
Esteva A;Kuprel B;Novoa RA;Ko J;Swetter SM;Blau HM;Thrun S
通讯作者：
Thrun S
DOI：
10.1016/j.yebeh.2018.10.013
发表时间：
2018-12
期刊：
Epilepsy & behavior : E&B
影响因子：
--
作者：
An S;Malhotra K;Dilley C;Han-Burgess E;Valdez JN;Robertson J;Clark C;Westover MB;Sun J
通讯作者：
Sun J
DOI：
10.4137/bii.s38308
发表时间：
2016
期刊：
Biomedical informatics insights
影响因子：
--
作者：
Cohen KB;Glass B;Greiner HM;Holland-Bouley K;Standridge S;Arya R;Faist R;Morita D;Mangano F;Connolly B;Glauser T;Pestian J
通讯作者：
Pestian J