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

Formative Evaluation of Digital Health Interventions (2375) Imaging Informatics (191) Clinical Information and Decision Making (1383) Machine Learning (1445) Surgery, Trauma and Surgical Sciences (142) Computer-Aided Diagnosis (119)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58776, first published .
A Deep Learning Model to Predict Breast Implant Texture Types Using Ultrasonography Images: Feasibility Development Study

A Deep Learning Model to Predict Breast Implant Texture Types Using Ultrasonography Images: Feasibility Development Study

A Deep Learning Model to Predict Breast Implant Texture Types Using Ultrasonography Images: Feasibility Development Study

Authors of this article:

Ho Heon Kim1 Author Orcid Image ;   Won Chan Jeong2 Author Orcid Image ;   Kyungran Pi3 Author Orcid Image ;   Angela Soeun Lee4 Author Orcid Image ;   Min Soo Kim4 Author Orcid Image ;   Hye Jin Kim4 Author Orcid Image ;   Jae Hong Kim5 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Ho Heon Kim   1 , MS ;   Won Chan Jeong   2 , BS ;   Kyungran Pi   3 , MS ;   Angela Soeun Lee   4 , MD ;   Min Soo Kim   4 , MD ;   Hye Jin Kim   4 , MD ;   Jae Hong Kim   5 , MD

1 Department of Biomedical Informatics, Medical School of Yonsei University, Seoul, Republic of Korea

2 3Billion, Inc, Seoul, Republic of Korea

3 Quantic EMBA, Washington, DC, United States

4 Korean Society of Breast Implant Research, Seoul, Republic of Korea

5 The W Clinic, Seoul, Republic of Korea

Corresponding Author:

  • Jae Hong Kim, MD
  • The W Clinic
  • 9F Kukdong B/D
  • 596 Gangnam-daero, Gangnam-gu
  • Seoul, 06038
  • Republic of Korea
  • Phone: 82 2-517-7617
  • Fax: 82 2-518-7617
  • Email: stenkaracin@gmail.com