首页> 外文期刊>Gastrointestinal Endoscopy >High pooled performance of convolutional neural networks in computer-aided diagnosis of GI ulcers and/or hemorrhage on wireless capsule endoscopy images: a systematic review and meta-analysis
【24h】

High pooled performance of convolutional neural networks in computer-aided diagnosis of GI ulcers and/or hemorrhage on wireless capsule endoscopy images: a systematic review and meta-analysis

机译:在无线胶囊内窥镜内窥镜检查中的计算机辅助性神经网络卷积神经网络的高集合性能和/或无线胶囊内窥镜检查的出血:系统评价和荟萃分析

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

Background and Aims: Diagnosis of GI ulcers and/or hemorrhage by wireless capsule endoscopy (WCE) is limited by the physician-dependent, tedious, time-consuming process of image and/ or video classification. Computer-aided diagnosis (CAD) by convolutional neural network (CNN)-based machine learning may help reduce this burden. Our aim was to conduct a meta-analysis and appraise the reported data.
机译:None

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号