Case-based repeatability and operating point variability of AI: breast lesion classification based on deep transfer learning

Author:

Whitney Heather M.,Drukker Karen,Abe Hiroyuki,Giger Maryellen L.

Publisher

SPIE

Reference16 articles.

1. Case-based repeatability of machine learning classification performance on breast MRI;Vieceli,2020

2. Repeatability profiles towards consistent sensitivity and specificity levels for machine learning on breast DCE-MRI;van Dusen,2020

3. Comparison of diagnostic performances, case-based repeatability, and operating sensitivity and specificity in classification of breast lesions using DCE-MRI;de Oliveira,2021

4. Amstutz, P., Drukker, K., Li, H., Abe, H., Giger, M. L. and Whitney, H. M., “Case-based diagnostic classification repeatability using radiomic features extracted from full-field digital mammography images of breast lesions,” Proc. SPIE 11597, Medical Imaging 2021: Computer-Aided Diagnosis, 115970X (2021).

5. Repeatability in computer-aided diagnosis: Application to breast cancer diagnosis on sonography

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3