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癫痫中的大数据分析与人工智能——通用数据模型分析以及基于机器学习的癫痫发作检测与预测

Big data analysis and artificial intelligence in epilepsy - common data model analysis and machine learning-based seizure detection and forecasting.

作者信息

Chung Yoon Gi, Jeon Yonghoon, Yoo Sooyoung, Kim Hunmin, Hwang Hee

机构信息

Division of Pediatric Neurology, Department of Pediatrics, Seoul National University Bundang Hospital, Seongnam, Korea.

R&D Center, ezCaretech Co., Ltd., Seoul, Korea.

出版信息

Clin Exp Pediatr. 2022 Jun;65(6):272-282. doi: 10.3345/cep.2021.00766. Epub 2021 Nov 26.

Abstract

There has been significant interest in big data analysis and artificial intelligence (AI) in medicine. Ever-increasing medical data and advanced computing power have enabled the number of big data analyses and AI studies to increase rapidly. Here we briefly introduce epilepsy, big data, and AI and review big data analysis using a common data model. Studies in which AI has been actively applied, such as those of electroencephalography epileptiform discharge detection, seizure detection, and forecasting, will be reviewed. We will also provide practical suggestions for pediatricians to understand and interpret big data analysis and AI research and work together with technical expertise.

摘要

医学领域对大数据分析和人工智能(AI)有着浓厚的兴趣。不断增长的医学数据和先进的计算能力使得大数据分析和AI研究的数量迅速增加。在此,我们简要介绍癫痫、大数据和AI,并使用通用数据模型回顾大数据分析。还将回顾积极应用AI的研究,如脑电图癫痫样放电检测、癫痫发作检测和预测等研究。我们还将为儿科医生提供实用建议,以帮助他们理解和解释大数据分析及AI研究,并与技术专家合作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/76df/9171464/45295a0dbe43/cep-2021-00766f1.jpg

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