Open AccessDevelopment and Validation of a Machine Learning Algorithm for Predicting Response to Anticholinergic Medications for Overactive Bladder Syndrome
Author(s) -
David Sheyn,
Mingxuan Ju,
Sixiao Zhang,
Caleb Anyaeche,
Adonis Hijaz,
Jeffrey Mangel,
Sahil Mahajan,
Britt Conroy,
Sherif A. El-Nashar,
Soumya Ray
Publication year - 2019
Publication title -
obstetrics and gynecology (new york. 1953. online)/obstetrics and gynecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.664
H-Index - 220
eISSN - 1873-233X
pISSN - 0029-7844
DOI - 10.1097/aog.0000000000003517
Subject(s) - anticholinergic , medicine , nocturia , overactive bladder , random forest , algorithm , area under the curve , urinary incontinence , receiver operating characteristic , machine learning , urology , urinary system , pathology , computer science , alternative medicine
To develop and externally validate a prediction model for anticholinergic response in patients with overactive bladder (OAB).