Title: Deep learning as a novel method for endoscopic diagnosis of chronic atrophic gastritis:
a prospective nested case-control study
Version: 3 Date: 14 Jul 2022
Reviewer's report:
Reviewer's report
Title: Deep learning as a novel method for endoscopic diagnosis of chronic atrophic
gastritis: a prospective nested case-control study
Reviewer's report:
General comments:
It's a meaningful work on the study of the endoscopic diagnosis in CAG based on U-Net
deep learning (DL). The authors have made careful revisions in the paper based on all the
comments. The revised paper is more appropriate in expression and more detailed in content.
So I recommend accepting the paper.
Quality of written English: Not needs some language corrections before being Published On
the whole.
Declaration of competing interests: I declare that I have no competing interests
Title: Deep learning as a novel method for endoscopic diagnosis of chronic atrophic gastritis:
a prospective nested case-control study
Version: 3 Date: 14 Jul 2022
Reviewer's report:
Reviewer's report
Title: Deep learning as a novel method for endoscopic diagnosis of chronic atrophic
gastritis: a prospective nested case-control study
Reviewer's report:
General comments:
It's a meaningful work on the study of the endoscopic diagnosis in CAG based on U-Net
deep learning (DL). The authors have made careful revisions in the paper based on all the
comments. The revised paper is more appropriate in expression and more detailed in content.
So I recommend accepting the paper.
Quality of written English: Not needs some language corrections before being Published On
the whole.
Declaration of competing interests: I declare that I have no competing interests
Please review this paper.
user
Title: Deep learning as a novel method for endoscopic diagnosis of chronic atrophic gastritis:
a prospective nested case-control study
Version: 3 Date: 14 Jul 2022
Reviewer's report:
Reviewer's report
Title: Deep learning as a novel method for endoscopic diagnosis of chronic atrophic
gastritis: a prospective nested case-control study
Reviewer's report:
General comments:
It's a meaningful work on the study of the endoscopic diagnosis in CAG based on U-Net
deep learning (DL). The authors have made careful revisions in the paper based on all the
comments. The revised paper is more appropriate in expression and more detailed in content.
So I recommend accepting the paper.
Quality of written English: Not needs some language corrections before being Published On
the whole.
Declaration of competing interests: I declare that I have no competing interests
assistant