论文标题

计算神经病学:痴呆中的计算建模方法

Computational neurology: Computational modeling approaches in dementia

论文作者

Wong-Lin, KongFatt, Sanchez-Bornot, Jose M., McCombe, Niamh, Kaur, Daman, McClean, Paula L., Zou, Xin, Youssofzadeh, Vahab, Ding, Xuemei, Bucholc, Magda, Yang, Su, Prasad, Girijesh, Coyle, Damien, Maguire, Liam P., Wang, Haiying, Wang, Hui, Atiya, Nadim A. A., Joshi, Alok

论文摘要

痴呆是与认知受损相关的症状集合,并阻碍了日常正常功能。痴呆症与阿尔茨海默氏病构成最常见的类型,在病因和病理生理学方面非常复杂。对痴呆研究或更普遍地在神经病学上的更定量或计算态度已成为必要的计算神经病学。我们对已经开发并应用于痴呆症研究的一些计算方法进行了重点审查,尤其是阿尔茨海默氏病。讨论了机械建模和数据驱动器(包括AI或机器学习)的方法。还将讨论与痴呆诊断的临床决策支持系统的联系。

Dementia is a collection of symptoms associated with impaired cognition and impedes everyday normal functioning. Dementia, with Alzheimer's disease constituting its most common type, is highly complex in terms of etiology and pathophysiology. A more quantitative or computational attitude towards dementia research, or more generally in neurology, is becoming necessary - Computational Neurology. We provide a focused review of some computational approaches that have been developed and applied to the study of dementia, particularly Alzheimer's disease. Both mechanistic modeling and data-drive, including AI or machine learning, approaches are discussed. Linkage to clinical decision support systems for dementia diagnosis will also be discussed.

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