Data-Driven Machine-Learning Quantifies Differences in the Voiding Initiation Network in Neurogenic Voiding Dysfunction in Women With Multiple Sclerosis

PURPOSE: To quantify the relative importance of brain regions responsible for reduced functional connectivity (FC) in their Voiding Initiation Network in female multiple sclerosis (MS) patients with neurogenic lower urinary tract dysfunction (NLUTD) and voiding dysfunction (VD). A data-driven machin...

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Detalles Bibliográficos
Autores principales: Karmonik, Christof, Boone, Timothy, Khavari, Rose
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Continence Society 2019
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6790826/
https://www.ncbi.nlm.nih.gov/pubmed/31607098
http://dx.doi.org/10.5213/inj.1938058.029

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6790826/
https://www.ncbi.nlm.nih.gov/pubmed/31607098
http://dx.doi.org/10.5213/inj.1938058.029

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