兰州大学学报（医学版）2025，Vol.51Issue(7)：9-14,6.DOI:10.13885/j.issn.2097-681X.2025.07.002
基于机器学习的男性膀胱出口梗阻诊断模型
A diagnostic model for male bladder outlet obstruction based on machine learning
摘要
Abstract
Objective To develop a machine learning diagnostic model for male bladder outlet obstruction.Methods Retrospective urodynamic studydata from 580 male patients(290 obstructive cases and 290 non-obstructive cases)at Tongji Hospital Affiliated To Tongji Medical College HUST(2019-2024)were collected using stratified sampling.Fifteen characteristic parameters were extracted to establish the dataset.Models with different feature combinations were constructed,trained and validated.Performance was evaluated using precision,recall,F1-score,accuracy and specificity.Results The model achieved optimal performance(area under the curve:0.95±0.02)with 11 selected features via five-fold cross-validation,significantly outper-forming traditional methods(Linearized Passive Urethral Resistance Relation and bladder outlet obstruction index).Conclusion The backpropagation neural network-based machine learning model demonstrates strong diagnostic performance for male bladder outlet obstruction.关键词
膀胱出口梗阻/尿动力学/机器学习/反向传播神经网络/特征提取/诊断模型Key words
bladder outlet obstruction/urodynamics/machine learning/backpropagation neural network/fea-ture extraction/diagnostic algorithm分类
医药卫生引用本文复制引用
杨正龙,胡友民,陈忠,周全..基于机器学习的男性膀胱出口梗阻诊断模型[J].兰州大学学报（医学版）,2025,51(7):9-14,6.基金项目
湖北省自然科学联合基金项目(2023AFD072) （2023AFD072）
华中科技大学创新与转化孵化项目(2022ZHFY11) （2022ZHFY11）
