9 March 2011 Differential spatial activity patterns of acupuncture by a machine learning based analysis
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Proceedings Volume 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging; 79651Q (2011); doi: 10.1117/12.877981
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States
Abstract
Acupoint specificity, lying at the core of the Traditional Chinese Medicine, underlies the theoretical basis of acupuncture application. However, recent studies have reported that acupuncture stimulation at nonacupoint and acupoint can both evoke similar signal intensity decreases in multiple regions. And these regions were spatially overlapped. We used a machine learning based Support Vector Machine (SVM) approach to elucidate the specific neural response pattern induced by acupuncture stimulation. Group analysis demonstrated that stimulation at two different acupoints (belong to the same nerve segment but different meridians) could elicit distinct neural response patterns. Our findings may provide evidence for acupoint specificity.
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Youbo You, Lijun Bai, Ting Xue, Chongguang Zhong, Zhenyu Liu, Jie Tian, "Differential spatial activity patterns of acupuncture by a machine learning based analysis", Proc. SPIE 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging, 79651Q (9 March 2011); doi: 10.1117/12.877981; https://doi.org/10.1117/12.877981
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KEYWORDS
Functional magnetic resonance imaging

Thalamus

Machine learning

Medicine

Brain

Head

Neuroimaging

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