Title: Machine Learning for Temporary Stoma After Intestinal Resection in Surgical Decision-
Making of Crohn's Disease
Version: 1 Date: 13 Sep 2024
Reviewer's report:
PEER REVIEWER ASSESSMENTS:
OBJECTIVE - Full research articles: is there a clear objective that addresses a testable research
question(s) (brief or other article types: is there a clear objective)?
Yes - there is a clear objective
DESIGN - Is the current approach (including controls and analysis protocols) appropriate for
the objective?
Yes - the approach is appropriate
EXECUTION - Are the experiments and analyses performed with technical rigor to allow
confidence in the results?
Yes - experiments and analyses were performed appropriately
STATISTICS - Is the use of statistics in the manuscript appropriate?
Yes - appropriate statistical analyses have been used in the study
INTERPRETATION - Is the current interpretation/discussion of the results reasonable and not
overstated?
Yes - the author's interpretation is reasonable
OVERALL MANUSCRIPT POTENTIAL - Is the current version of this work technically
sound? If not, can revisions be made to make the work technically sound?
Yes - current version is technically sound
PEER REVIEWER COMMENTS:
GENERAL COMMENTS: The authors present a manuscript about A Predictive Nomogram
Model for Temporary Stoma After Intestinal Resection in Surgical Decision-Making of Crohn's
Disease. The analysis is very promising and the data are well presented. Crohn’s disease remains
a main topic in general surgery. The overall impression is that the manuscript sounds well. It
is technically written. It provides important considerations about when to perform a temporary
stoma after intestinal resection.
It is as manuscript that gives reasonable help about the decision when to perform a temporary
stoma after intestinal resection. It sounds well and the data interpretation is conducted
scientifically. It contributes greatly in the field of IBD disease specially when it needs of surgical
intervention. The results should be widely used in routine decision making.
Title: Machine Learning for Temporary Stoma After Intestinal Resection in Surgical Decision-
Making of Crohn's Disease
Version: 1 Date: 13 Sep 2024
Reviewer's report:
PEER REVIEWER ASSESSMENTS:
OBJECTIVE - Full research articles: is there a clear objective that addresses a testable research
question(s) (brief or other article types: is there a clear objective)?
Yes - there is a clear objective
DESIGN - Is the current approach (including controls and analysis protocols) appropriate for
the objective?
Yes - the approach is appropriate
EXECUTION - Are the experiments and analyses performed with technical rigor to allow
confidence in the results?
Yes - experiments and analyses were performed appropriately
STATISTICS - Is the use of statistics in the manuscript appropriate?
Yes - appropriate statistical analyses have been used in the study
INTERPRETATION - Is the current interpretation/discussion of the results reasonable and not
overstated?
Yes - the author's interpretation is reasonable
OVERALL MANUSCRIPT POTENTIAL - Is the current version of this work technically
sound? If not, can revisions be made to make the work technically sound?
Yes - current version is technically sound
PEER REVIEWER COMMENTS:
GENERAL COMMENTS: The authors present a manuscript about A Predictive Nomogram
Model for Temporary Stoma After Intestinal Resection in Surgical Decision-Making of Crohn's
Disease. The analysis is very promising and the data are well presented. Crohn’s disease remains
a main topic in general surgery. The overall impression is that the manuscript sounds well. It
is technically written. It provides important considerations about when to perform a temporary
stoma after intestinal resection.
It is as manuscript that gives reasonable help about the decision when to perform a temporary
stoma after intestinal resection. It sounds well and the data interpretation is conducted
scientifically. It contributes greatly in the field of IBD disease specially when it needs of surgical
intervention. The results should be widely used in routine decision making.
Please review this paper.
user
Title: Machine Learning for Temporary Stoma After Intestinal Resection in Surgical Decision-
Making of Crohn's Disease
Version: 1 Date: 13 Sep 2024
Reviewer's report:
PEER REVIEWER ASSESSMENTS:
OBJECTIVE - Full research articles: is there a clear objective that addresses a testable research
question(s) (brief or other article types: is there a clear objective)?
Yes - there is a clear objective
DESIGN - Is the current approach (including controls and analysis protocols) appropriate for
the objective?
Yes - the approach is appropriate
EXECUTION - Are the experiments and analyses performed with technical rigor to allow
confidence in the results?
Yes - experiments and analyses were performed appropriately
STATISTICS - Is the use of statistics in the manuscript appropriate?
Yes - appropriate statistical analyses have been used in the study
INTERPRETATION - Is the current interpretation/discussion of the results reasonable and not
overstated?
Yes - the author's interpretation is reasonable
OVERALL MANUSCRIPT POTENTIAL - Is the current version of this work technically
sound? If not, can revisions be made to make the work technically sound?
Yes - current version is technically sound
PEER REVIEWER COMMENTS:
GENERAL COMMENTS: The authors present a manuscript about A Predictive Nomogram
Model for Temporary Stoma After Intestinal Resection in Surgical Decision-Making of Crohn's
Disease. The analysis is very promising and the data are well presented. Crohn’s disease remains
a main topic in general surgery. The overall impression is that the manuscript sounds well. It
is technically written. It provides important considerations about when to perform a temporary
stoma after intestinal resection.
It is as manuscript that gives reasonable help about the decision when to perform a temporary
stoma after intestinal resection. It sounds well and the data interpretation is conducted
scientifically. It contributes greatly in the field of IBD disease specially when it needs of surgical
intervention. The results should be widely used in routine decision making.
assistant