This paper is in the following e-collection/theme issue:

Decision Support for Health Professionals (1210) Imaging Informatics (200) Breast Cancer (213) Innovations and Technology for Cancer Prevention and Screening (150) Innovations and Technology in Cancer Care (431) Innovations in Cancer Diagnostic and Decision Support (58)

Published on in Vol 8, No 3 (2020): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16334, first published .
Performance of Computer-Aided Diagnosis in Ultrasonography for Detection of Breast Lesions Less and More Than 2 cm: Prospective Comparative Study

Performance of Computer-Aided Diagnosis in Ultrasonography for Detection of Breast Lesions Less and More Than 2 cm: Prospective Comparative Study

Performance of Computer-Aided Diagnosis in Ultrasonography for Detection of Breast Lesions Less and More Than 2 cm: Prospective Comparative Study

Authors of this article:

Liang Yongping1 Author Orcid Image ;   Ping Zhou1 Author Orcid Image ;   Zhang Juan1 Author Orcid Image ;   Zhao Yongfeng1 Author Orcid Image ;   Wengang Liu1 Author Orcid Image ;   Yifan Shi1 Author Orcid Image
Article Authors Cited by (4) Tweetations (1) Metrics

Journals

  1. Yongping L, Juan Z, Zhou P, Yongfeng Z, Liu W, Shi Y. Evaluation of the Quadri-Planes Method in Computer-Aided Diagnosis of Breast Lesions by Ultrasonography: Prospective Single-Center Study. JMIR Medical Informatics 2020;8(5):e18251 View
  2. Kim M, Kim S, Kim Y, Kim E, Chang J. Added value of deep learning-based computer-aided diagnosis and shear wave elastography to b-mode ultrasound for evaluation of breast masses detected by screening ultrasound. Medicine 2021;100(31):e26823 View
  3. Zhang P, Zhang M, Lu M, Jin C, Wang G, Lin X. Comparative Analysis of the Diagnostic Value of S-Detect Technology in Different Planes Versus the BI-RADS Classification for Breast Lesions. Academic Radiology 2024 View
  4. Du L, Liu H, Cai M, Pan J, Zha H, Nie C, Lin M, Li C, Zong M, Zhang B. Ultrasound S-detect system can improve diagnostic performance of less experienced radiologists in differentiating breast masses: a retrospective dual-centre study. British Journal of Radiology 2024 View