Identifying Bladder Phenotypes After Spinal Cord Injury With Unsupervised Machine Learning: A New Way to Examine Urinary Symptoms and Quality of Life.

Abstract excerpt

PURPOSE: Patients with spinal cord injuries (SCIs) experience variable urinary symptoms and quality of life (QOL). Our objective was to use machine learning to identify bladder-relevant phenotypes after SCI and assess their association with urinary symptoms and QOL. MATERIALS AND METHODS: We used data from the Neurogenic Bladder Research Group SCI registry. Baseline variables that were previously shown to be...

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