Multivariate Pattern Analysis of Lifelong Premature Ejaculation Based on Multiple Kernel Support Vector Machine

OBJECTIVE: This study aimed to develop an effective support vector machine (SVM) classifier based on the multi-modal data for detecting the main brain networks involved in group separation of premature ejaculation (PE). METHODS: A total of fifty-two patients with lifelong PE and 36 matched healthy c...

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Detalles Bibliográficos
Autores principales: Geng, Bowen, Gao, Ming, Piao, Ruiqing, Liu, Chengxiang, Xu, Ke, Zhang, Shuming, Zeng, Xiao, Liu, Peng, Wang, Yanzhu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Psychiatry
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357875/
https://www.ncbi.nlm.nih.gov/pubmed/35958632
http://dx.doi.org/10.3389/fpsyt.2022.906404

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357875/
https://www.ncbi.nlm.nih.gov/pubmed/35958632
http://dx.doi.org/10.3389/fpsyt.2022.906404

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