Artificial intelligence-based prediction of treatment failure and medication nonadherence in overactive bladder management

BAŞARANOĞLU,MERT | TAŞDEMİR,İSA KAMİL | AKBAY,ERDEM | DORUK,HASAN ERDAL

Abstract , Background Overactive bladder management presents significant challenges, with treatment failures and medication non-adherence posing substantial barriers to patient outcomes. Early prediction of these challenges could enable timely interventions and treatment modifications. Objectives To develop and validate an artificial intelligence-based prediction model for early identification of treatment failure and medication non-adherence in overactive bladder patients, with specific focus on different pathological subgroups including diabetic neuropathy. Methods In this single-center retrospective study (January 2018–April 2025), we analyzed data from 285 patients with overactive bladder. We developed and validated artificial intelligence models using comprehensive clinical parameters...