Can we use machine learning to improve the interpretation and application of urodynamic data?: International Consultation on Incontinence-Research Society 2023.

Andrew Gammie Salvador Arlandis Bruna M Couri Michael Drinnan Carolina D Ochoa Angela Rantell Mathijs M de Rijk Thomas R F van Steenbergen Margot S Damaser

Published in: Neurourology and urodynamics (2023)

ML is well suited to the analysis of urodynamic data, but results to date have not achieved clinical utility. It is considered likely that further research can improve the analysis of the large, multifactorial data sets generated by urodynamic clinics, and improve to some extent data pattern recognition that is currently subject to observer error and artefactual noise.

Keyphrases

electronic health record
big data
machine learning
urinary incontinence
lower urinary tract symptoms
primary care
palliative care
benign prostatic hyperplasia