信息工程大学学报2024，Vol.25Issue(3)：265-271,7.DOI:10.3969/j.issn.1671-0673.2024.03.003
基于Mixup训练及多模型决策融合的腰椎间盘突出诊断
Diagnosis of Lumbar Disc Herniation Based on Mixup Training and Decision Fusion of Multiple Models
李英 1陈健 1苏志海 2海金金 1闫镔1
作者信息
- 1. 信息工程大学,河南 郑州 450001
- 2. 中山大学附属第五医院脊柱外科,广东 珠海 519000
- 折叠
摘要
Abstract
The distribution of multi-center medical datasets is different,and the generalization of the model trained by single-center datasets is often poor,resulting in great limitations in application.Mixup training can effectively improve the generalization of the model,and the model fusion method based on Dempster-Shafer evidence theory(DST)can effectively fuse the best decision of multiple mod-els.Therefore,we propose an effective model for the diagnosis of lumbar disc herniation in response to the poor generalization of medical models trained by single-center datasets.The generalization of the model is enhanced by Mixup training,and the best decision is obtained by the method of multi-model decision fusion based on DST.After testing on the external test set,the method obtains 88.22%classifi-cation accuracy,88.12%F1 score and AUC value of 87.69%.关键词
腰椎核磁影像/腰椎间盘突出诊断/Mixup/多模型决策融合Key words
lumbar magnetic resonance imaging/lumbar disc herniation/Mixup/multi-model fu-sion decision分类
信息技术与安全科学引用本文复制引用
李英,陈健,苏志海,海金金,闫镔..基于Mixup训练及多模型决策融合的腰椎间盘突出诊断[J].信息工程大学学报,2024,25(3):265-271,7.
