Machine Learning in Neuroimaging: A New Approach to Understand Acupuncture for Neuroplasticity
Joint Authors
He, Zhaoxuan
Sun, Ruirui
Ma, Peihong
Zeng, Fang
Yin, Tao
Tian, Zilei
Xie, Kunnan
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-24
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
The effects of acupuncture facilitating neural plasticity for treating diseases have been identified by clinical and experimental studies.
In the last two decades, the application of neuroimaging techniques in acupuncture research provided visualized evidence for acupuncture promoting neuroplasticity.
Recently, the integration of machine learning (ML) and neuroimaging techniques becomes a focus in neuroscience and brings a new and promising approach to understand the facilitation of acupuncture on neuroplasticity at the individual level.
This review is aimed at providing an overview of this rapidly growing field by introducing the commonly used ML algorithms in neuroimaging studies briefly and analyzing the characteristics of the acupuncture studies based on ML and neuroimaging, so as to provide references for future research.
American Psychological Association (APA)
Yin, Tao& Ma, Peihong& Tian, Zilei& Xie, Kunnan& He, Zhaoxuan& Sun, Ruirui…[et al.]. 2020. Machine Learning in Neuroimaging: A New Approach to Understand Acupuncture for Neuroplasticity. Neural Plasticity،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1203053
Modern Language Association (MLA)
Yin, Tao…[et al.]. Machine Learning in Neuroimaging: A New Approach to Understand Acupuncture for Neuroplasticity. Neural Plasticity No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1203053
American Medical Association (AMA)
Yin, Tao& Ma, Peihong& Tian, Zilei& Xie, Kunnan& He, Zhaoxuan& Sun, Ruirui…[et al.]. Machine Learning in Neuroimaging: A New Approach to Understand Acupuncture for Neuroplasticity. Neural Plasticity. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1203053
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1203053