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

Artificial Intelligence (1430) Imaging Informatics (202) Machine Learning (1505)

Published on in Vol 22, No 11 (2020): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18563, first published .
Automated Diagnosis of Various Gastrointestinal Lesions Using a Deep Learning–Based Classification and Retrieval Framework With a Large Endoscopic Database: Model Development and Validation

Automated Diagnosis of Various Gastrointestinal Lesions Using a Deep Learning–Based Classification and Retrieval Framework With a Large Endoscopic Database: Model Development and Validation

Automated Diagnosis of Various Gastrointestinal Lesions Using a Deep Learning–Based Classification and Retrieval Framework With a Large Endoscopic Database: Model Development and Validation

Authors of this article:

Muhammad Owais1 Author Orcid Image ;   Muhammad Arsalan1 Author Orcid Image ;   Tahir Mahmood1 Author Orcid Image ;   Jin Kyu Kang1 Author Orcid Image ;   Kang Ryoung Park1 Author Orcid Image
Article Authors Cited by (17) Tweetations (4) Metrics

Muhammad Owais   1 , MSc ;   Muhammad Arsalan   1 , PhD ;   Tahir Mahmood   1 , MSc ;   Jin Kyu Kang   1 , BSc ;   Kang Ryoung Park   1 , PhD

1 Division of Electronics and Electrical Engineering, Dongguk University, Seoul, Republic of Korea

Corresponding Author:

  • Kang Ryoung Park, PhD
  • Division of Electronics and Electrical Engineering
  • Dongguk University
  • 30 Pildong-ro 1-gil, Jung-gu
  • Seoul, 04620
  • Republic of Korea
  • Phone: 82 10-3111-7022
  • Fax: 82 2-2277-8735
  • Email: parkgr@dgu.edu