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

CONCLUSION: Voiders and VD patients showed distinctly different FC in their Voiding Initiation Network. Machine-learning is able to identify brain centers contributing to these observed differences. Knowledge of these centers and their connectivity may allow phenotyping patients to centrally focused treatments such as cortical modulation. PMID: 31607098 [PubMed]
Source: International Neurourology Journal - Category: Urology & Nephrology Tags: Int Neurourol J Source Type: research