Title: A newly developed deep learning-based system for automatic detection and classification
of small bowel lesions during double-balloon enteroscopy examination
Version: 2 Date: 26 Jun 2023
Reviewer's report:
Dear authors,
I believe the topic to be very interesting and relevant. The concept of developing a computer-
aided diagnostic that is able to identify different categories of pathology, as well as the methods
of developing a gold standard by 3 DBE-experts; and investigating the interobserver variation
are well developed.
My foremost comment is that the article is not well-written, with occasionally the wrong word,
as well as repeat information in the different sections. I would recommend a language review
by a native English speaker.
Secondly, I find it unclear who developed the algorithm, as most medical doctors do not have
the knowledge and experience needed, and nothing in the author contributions described who
developed and adjusted the algorithm.
The third major comment is that I find the discussion to be superficial and mainly focusing on
your nice results, I would love a more thorough assessment and rebuttal of the limitations of the
study. I would suggest to describe how your results compare to similar studies, an assessment
of limitations and an assessment of strengths of your study, followed by future perspectives.
Specific comments on the article:
The abstract does not describe the gold standard you developed, which is very relevant for the
whole article and should be mentioned in my opinion.
In the method section: is it really a retrospective study? I suppose I would call it an interobserver
study, comparing assessments of the CAD and human readers.
Were the images and videos collected retrospectively, or prospectively?
Why did you only select abnormal images in model2? I gather that some DBE-investigations
are without pathology, or multiple different lesions? Wouldn't it be important to detect all these
kind of real-life results? (Could be one of the limitations you comment on in your discussion.)
Why present percentages with 2 decimals, I do not believe it makes a difference in the results,
and it does make it harder to read the text with the extra decimals.
I would propose presenting supplementary table 5 and 6 in your results, since it is one of the
main results of your study.
Results: I do not appreciate the &-sign in your written text, would prefer a `,` or `and`.
Why not discuss in your discussion the lower accuracy of detection of erosions and ulcers by
the ENDOANGEL-DBE? (It appears to be significantly lower than the other pathologies)
Supplementery table 1: I doubt whether it is relevant what the age and sex of the different patients
are, can possibly be removed.
Supplementary figure 2: specify who misdiagnosed what as what, unclear from the current text.
Possibly figure 3 as a supplemental figure, is not as relevant as the videos in my opinion.
Figure 4 holds the same images as figure 1, why not remove it or add to supplemental figures?
Title: A newly developed deep learning-based system for automatic detection and classification
of small bowel lesions during double-balloon enteroscopy examination
Version: 2 Date: 26 Jun 2023
Reviewer's report:
Dear authors,
I believe the topic to be very interesting and relevant. The concept of developing a computer-
aided diagnostic that is able to identify different categories of pathology, as well as the methods
of developing a gold standard by 3 DBE-experts; and investigating the interobserver variation
are well developed.
My foremost comment is that the article is not well-written, with occasionally the wrong word,
as well as repeat information in the different sections. I would recommend a language review
by a native English speaker.
Secondly, I find it unclear who developed the algorithm, as most medical doctors do not have
the knowledge and experience needed, and nothing in the author contributions described who
developed and adjusted the algorithm.
The third major comment is that I find the discussion to be superficial and mainly focusing on
your nice results, I would love a more thorough assessment and rebuttal of the limitations of the
study. I would suggest to describe how your results compare to similar studies, an assessment
of limitations and an assessment of strengths of your study, followed by future perspectives.
Specific comments on the article:
The abstract does not describe the gold standard you developed, which is very relevant for the
whole article and should be mentioned in my opinion.
In the method section: is it really a retrospective study? I suppose I would call it an interobserver
study, comparing assessments of the CAD and human readers.
Were the images and videos collected retrospectively, or prospectively?
Why did you only select abnormal images in model2? I gather that some DBE-investigations
are without pathology, or multiple different lesions? Wouldn't it be important to detect all these
kind of real-life results? (Could be one of the limitations you comment on in your discussion.)
Why present percentages with 2 decimals, I do not believe it makes a difference in the results,
and it does make it harder to read the text with the extra decimals.
I would propose presenting supplementary table 5 and 6 in your results, since it is one of the
main results of your study.
Results: I do not appreciate the &-sign in your written text, would prefer a `,` or `and`.
Why not discuss in your discussion the lower accuracy of detection of erosions and ulcers by
the ENDOANGEL-DBE? (It appears to be significantly lower than the other pathologies)
Supplementery table 1: I doubt whether it is relevant what the age and sex of the different patients
are, can possibly be removed.
Supplementary figure 2: specify who misdiagnosed what as what, unclear from the current text.
Possibly figure 3 as a supplemental figure, is not as relevant as the videos in my opinion.
Figure 4 holds the same images as figure 1, why not remove it or add to supplemental figures?
Please review this paper.
user
Title: A newly developed deep learning-based system for automatic detection and classification
of small bowel lesions during double-balloon enteroscopy examination
Version: 2 Date: 26 Jun 2023
Reviewer's report:
Dear authors,
I believe the topic to be very interesting and relevant. The concept of developing a computer-
aided diagnostic that is able to identify different categories of pathology, as well as the methods
of developing a gold standard by 3 DBE-experts; and investigating the interobserver variation
are well developed.
My foremost comment is that the article is not well-written, with occasionally the wrong word,
as well as repeat information in the different sections. I would recommend a language review
by a native English speaker.
Secondly, I find it unclear who developed the algorithm, as most medical doctors do not have
the knowledge and experience needed, and nothing in the author contributions described who
developed and adjusted the algorithm.
The third major comment is that I find the discussion to be superficial and mainly focusing on
your nice results, I would love a more thorough assessment and rebuttal of the limitations of the
study. I would suggest to describe how your results compare to similar studies, an assessment
of limitations and an assessment of strengths of your study, followed by future perspectives.
Specific comments on the article:
The abstract does not describe the gold standard you developed, which is very relevant for the
whole article and should be mentioned in my opinion.
In the method section: is it really a retrospective study? I suppose I would call it an interobserver
study, comparing assessments of the CAD and human readers.
Were the images and videos collected retrospectively, or prospectively?
Why did you only select abnormal images in model2? I gather that some DBE-investigations
are without pathology, or multiple different lesions? Wouldn't it be important to detect all these
kind of real-life results? (Could be one of the limitations you comment on in your discussion.)
Why present percentages with 2 decimals, I do not believe it makes a difference in the results,
and it does make it harder to read the text with the extra decimals.
I would propose presenting supplementary table 5 and 6 in your results, since it is one of the
main results of your study.
Results: I do not appreciate the &-sign in your written text, would prefer a `,` or `and`.
Why not discuss in your discussion the lower accuracy of detection of erosions and ulcers by
the ENDOANGEL-DBE? (It appears to be significantly lower than the other pathologies)
Supplementery table 1: I doubt whether it is relevant what the age and sex of the different patients
are, can possibly be removed.
Supplementary figure 2: specify who misdiagnosed what as what, unclear from the current text.
Possibly figure 3 as a supplemental figure, is not as relevant as the videos in my opinion.
Figure 4 holds the same images as figure 1, why not remove it or add to supplemental figures?
assistant