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

Artificial Intelligence (1430) Computer-Aided Diagnosis (136) Imaging Informatics (202)

Published on in Vol 22, No 9 (2020): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21983, first published .
Artificial Intelligence for the Prediction of Helicobacter Pylori Infection in Endoscopic Images: Systematic Review and Meta-Analysis Of Diagnostic Test Accuracy

Artificial Intelligence for the Prediction of Helicobacter Pylori Infection in Endoscopic Images: Systematic Review and Meta-Analysis Of Diagnostic Test Accuracy

Artificial Intelligence for the Prediction of Helicobacter Pylori Infection in Endoscopic Images: Systematic Review and Meta-Analysis Of Diagnostic Test Accuracy

Authors of this article:

Chang Seok Bang1, 2, 3, 4 Author Orcid Image ;   Jae Jun Lee3, 4, 5 Author Orcid Image ;   Gwang Ho Baik1, 2 Author Orcid Image
Article Authors Cited by (63) Tweetations (4) Metrics

Chang Seok Bang   1, 2, 3, 4 , MD, PhD ;   Jae Jun Lee   3, 4, 5 , MD ;   Gwang Ho Baik   1, 2 , MD

1 Department of Internal Medicine, Hallym University College of Medicine, Chuncheon, Republic of Korea

2 Institute for Liver and Digestive Diseases, Hallym University, Chuncheon, Republic of Korea

3 Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon, Republic of Korea

4 Division of Big Data and Artificial Intelligence, Chuncheon Sacred Heart Hospital, Chuncheon, Republic of Korea

5 Department of Anesthesiology and Pain Medicine, Hallym University College of Medicine, Chuncheon, Republic of Korea

Corresponding Author:

  • Chang Seok Bang, MD, PhD
  • Department of Internal Medicine
  • Hallym University College of Medicine
  • Sakju-ro 77
  • Chuncheon
  • Republic of Korea
  • Phone: 82 33 240 5000
  • Fax: 82 33 241 8064
  • Email: csbang@hallym.ac.kr