Digital Twin Models for Personalised and Predictive Medicine in Ophthalmology

Round 1

Reviewer 1 Report

This paper researches a digital twin models for personalized and predictive medicine in ophthalmology, give an architectural framework for digital twin, risks and vulnerabilities. The research of this paper has some significance, but there are many shortcomings in this paper, which are as follows:

(1) The specific principle is not clearly explained by the author about digital twin models for personalized and predictive medicine. The author only gives a general description, and it is suggested that the author give a detailed principle and method according to the research object.

(2) in part 3.2, the authors describe the vulnerabilities at the digital twin level, how to improve the method? What are the specific measures?

(3) in part 5 and 6, although the author gives some analysis and results, there is no corresponding model in the method section.

(4) The author introduces a deep learning method, but does not give a specific model, and suggests that the author give a suitable model that conforms to the method proposed in this paper.

(5) This paper lacks comparative validation of research methods.

The expression of the paper is relatively good, but the description of some sentence needs further improvement

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Please, refere to the attached document for comments.

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Thank you for considering the remarks and integrating them in extensive re-work.