Machine Learning Models for the Noninvasive Diagnosis of Bladder Outlet Obstruction and Detrusor Underactivity in Men With Lower Urinary Tract Symptoms

Purpose This study aimed to develop and evaluate machine learning models, specifically CatBoost and extreme gradient boosting (XGBoost), for diagnosing lower urinary tract symptoms (LUTS) in male patients. The objective is to differentiate between bladder outlet obstruction (BOO) and detrusor undera...

وصف كامل

التفاصيل البيبلوغرافية

المؤلفون الرئيسيون:	Hyungkyung Shin, Kwang Jin Ko, Wei-Jin Park, Deok Hyun Han, Ikjun Yeom, Kyu-Sung Lee
التنسيق:	Artigo
اللغة:	Inglês
منشور في:	Korean Continence Society 2024-11-01
سلاسل:	International Neurourology Journal
الموضوعات:	artificial intelligence bladder outlet obstruction diagnosis lower urinary tract symptoms urinary bladder, underactive
الوصول للمادة أونلاين:	http://einj.org/upload/pdf/inj-2448360-180.pdf
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!