Title:  Development and clinical validation of deep learning-based Immunohistochemistry
prediction models for subtyping and staging of gastrointestinal cancers
Version: 5 Date: 01 May 2025
Reviewer's report:
1. I still do not really understand the main purpose of this study. It is emphasized that some
facilities lack pathologists, therefore, this would be able to make up for that. My question is, who
takes responsibility for the results interpreted by AI? The developer of the program? You, who
have positive results? If not, but the remaining and small number of pathologists, then it means
double work. And as a pathologist, I can tell you, that I would not sign out a histopathology
report without checking the IHC for myself. For me, examination of an IHC slide takes 5-10
s. Here, you have to annotate and "digest" the slide with AI, then somehow assess the results.
It is simply not practical or worth it at all. I think this is a fundamental error in the study, not
considering what would be the ACTUAL value of something you try to work on/with.
2. The ethical approval's number is not presented in the manuscript text.
3. The changes I suggested have been carried out.
4. With these statistical results, it is hard to interpret the pathologists' opinion in the text. Surely,
it may due to the fact that they are included in the article, and they spent a lot of time with this
study, and would like it to be published. However, if you consider the above mentioned details,
no pathologist who does not have a conflict interest in studies like these would trust/suggest AI
in the interpretation of IHC.
5. List of abbreviations is still not in alphabetic order.
6. P53 is often detailed as overexpressed and null phenotype, instead of mutant and null.
7. "The performance of AI-IHC is great in the test sets and we visualize the AI output at the
molecular level." - No, you did not perform this analysis on a molecular level.
8. Reference list is still presented in another lettering type. Maybe due to some program that
was used.
Title:  Development and clinical validation of deep learning-based Immunohistochemistry
prediction models for subtyping and staging of gastrointestinal cancers
Version: 5 Date: 01 May 2025
Reviewer's report:
1. I still do not really understand the main purpose of this study. It is emphasized that some
facilities lack pathologists, therefore, this would be able to make up for that. My question is, who
takes responsibility for the results interpreted by AI? The developer of the program? You, who
have positive results? If not, but the remaining and small number of pathologists, then it means
double work. And as a pathologist, I can tell you, that I would not sign out a histopathology
report without checking the IHC for myself. For me, examination of an IHC slide takes 5-10
s. Here, you have to annotate and "digest" the slide with AI, then somehow assess the results.
It is simply not practical or worth it at all. I think this is a fundamental error in the study, not
considering what would be the ACTUAL value of something you try to work on/with.
2. The ethical approval's number is not presented in the manuscript text.
3. The changes I suggested have been carried out.
4. With these statistical results, it is hard to interpret the pathologists' opinion in the text. Surely,
it may due to the fact that they are included in the article, and they spent a lot of time with this
study, and would like it to be published. However, if you consider the above mentioned details,
no pathologist who does not have a conflict interest in studies like these would trust/suggest AI
in the interpretation of IHC.
5. List of abbreviations is still not in alphabetic order.
6. P53 is often detailed as overexpressed and null phenotype, instead of mutant and null.
7. "The performance of AI-IHC is great in the test sets and we visualize the AI output at the
molecular level." - No, you did not perform this analysis on a molecular level.
8. Reference list is still presented in another lettering type. Maybe due to some program that
was used.
Please review this paper.
user
Title:  Development and clinical validation of deep learning-based Immunohistochemistry
prediction models for subtyping and staging of gastrointestinal cancers
Version: 5 Date: 01 May 2025
Reviewer's report:
1. I still do not really understand the main purpose of this study. It is emphasized that some
facilities lack pathologists, therefore, this would be able to make up for that. My question is, who
takes responsibility for the results interpreted by AI? The developer of the program? You, who
have positive results? If not, but the remaining and small number of pathologists, then it means
double work. And as a pathologist, I can tell you, that I would not sign out a histopathology
report without checking the IHC for myself. For me, examination of an IHC slide takes 5-10
s. Here, you have to annotate and "digest" the slide with AI, then somehow assess the results.
It is simply not practical or worth it at all. I think this is a fundamental error in the study, not
considering what would be the ACTUAL value of something you try to work on/with.
2. The ethical approval's number is not presented in the manuscript text.
3. The changes I suggested have been carried out.
4. With these statistical results, it is hard to interpret the pathologists' opinion in the text. Surely,
it may due to the fact that they are included in the article, and they spent a lot of time with this
study, and would like it to be published. However, if you consider the above mentioned details,
no pathologist who does not have a conflict interest in studies like these would trust/suggest AI
in the interpretation of IHC.
5. List of abbreviations is still not in alphabetic order.
6. P53 is often detailed as overexpressed and null phenotype, instead of mutant and null.
7. "The performance of AI-IHC is great in the test sets and we visualize the AI output at the
molecular level." - No, you did not perform this analysis on a molecular level.
8. Reference list is still presented in another lettering type. Maybe due to some program that
was used.
assistant