机器学习在老年轻度认知障碍识别中的研究进展

Advances in Machine Learning for Mild Cognitive Impairment Recognition in the Elderly

轻度认知障碍(MCI)作为痴呆的前临床阶段,被广泛认为是痴呆防治重要领域。随着我国人口老龄化速度加快,老年人口MCI的患病率也逐年上升。近年来,机器学习因其强大的数据处理和挖掘能力逐渐被应用到痴呆早期筛查中。本文从机器学习在MCI方面的研究现状进行介绍,对机器学习算法在老年轻度障碍中的数据采集、特征选择、研究优势以及研究进程等方面进行综合评述,进一步增加研究学者对机器学习在老年轻度认知障碍中的关注并总结现阶段研究局限,对未来研究做出展望。

Mild cognitive impairment (MCI), as a preclinical stage of dementia, is widely recognized as an im-portant area of dementia prevention and treatment. With the accelerated rate of population aging in China, the prevalence of MCI in the elderly population has been increasing year by year. In recent years, machine learning has been gradually applied to dementia early screening due to its powerful data processing and mining capabilities. This paper introduces the current research status of ma-chine learning in MCI, provides a comprehensive review of the data collection, feature selection, re-search advantages, and research process of machine learning algorithms in elderly mild impair-ment, further increases the attention of research scholars to machine learning in elderly mild cog-nitive impairment and summarizes the limitations of the current stage of the study, and makes an outlook of future research.