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Article
Peer-Review Record

Improvement of Auxiliary Diagnosis of Diabetic Cardiovascular Disease Based on Data Oversampling and Deep Learning

Appl. Sci. 2023, 13(9), 5449; https://doi.org/10.3390/app13095449
by Weiming Yang †, Yujia Guo † and Yuliang Liu *
Reviewer 1:
Reviewer 2:
Reviewer 4:
Appl. Sci. 2023, 13(9), 5449; https://doi.org/10.3390/app13095449
Submission received: 13 March 2023 / Revised: 24 April 2023 / Accepted: 25 April 2023 / Published: 27 April 2023
(This article belongs to the Special Issue Deep Learning and Machine Learning in Biomedical Data)

Round 1

Reviewer 1 Report

Please see the attached PDF file.

Comments for author File: Comments.pdf

Author Response

Dear Reviewer,

  Thank you very much for taking your time to review this manuscript. I really appreciate all your comments and suggestions! Please find my itemized responses in the attchment, and my revisions are highlighted in red in the resubmitted manuscript.

Thanks again.

Author Response File: Author Response.pdf

Reviewer 2 Report

Authors have a nice manuscript on a hot topic. They have good results on deep learning used for detecting cardiovascular disease among diabetic patients.

The manuscript would benefit writing out appendixes as they first appear in the text also each of the figure and table should include explanation of appendix used as well as more detailed legend. This varies and some of the legends are detailed but some lack more details. This concerns also the explanations for the appendix use in the table or figure.

Introduction is most parts nice and detailed. I think last paragraphs might be more in place if located in materials and methods.

These are minor concerns.

Author Response

Dear Reviewer,

  Thanks for your appreciation on our work. We have revised the manuscript according to your suggestion, and our revisions are highlighted in red in the resubmitted manuscript. Please review.

Thanks again.

Author Response File: Author Response.pdf

Reviewer 3 Report

The paper with the title " Auxiliary diagnosis of diabetic cardiovascular diseases by Data sampling and enhanced based on deep learning” is well written, interesting to read and presents a new approach into this field.

 

It is an interesting topic and I believe that the proposed algorithm can be used for the prediction of diabetic cardiovascular disease, with a role in improving the diagnosis of diseases. Making an intelligent medical diagnosis will reduce the workload of the clinician.

The results of the manuscript can represent a starting point for further research.

My comments are only intended to make the paper better. Good luck!

Author Response

Dear Reviewer,
    Thanks for your appreciation on our work. We will strive to research more effective methods to obtain better results. We have made further modifications to the manuscript, and our revisions are highlighted in red in the resubmitted manuscript. Please review.
Thanks again.

Author Response File: Author Response.pdf

Reviewer 4 Report

This article is an important part of importance of  the efficiency of clinical diagnosis of diabetic cardiovascular disease, which is conducive to the early detection and treatment of diseases.Cardiovascular diseases have a very important role in the diabetic complications and there have also a clinical implication in prognostic and follow up of diabetic patients.

The aim of this review article has a clinical relevance : the authors propose data oversampling synthesis techniques based on weights and extension algorithms.For this aim  where  included all relevant references, the research design  is appropriate,the methods  are adequately described and the conclusions supported by the results.

The article has a plus of scientific relevance by originality, and a high interest to the readers, The algorithm is clear and proove a high significance of content.

 I accept and recommande this article to doctors with diabetic, internist, nephrologist, cardiologist speciality

         
         
         
         
         
 

 

Author Response

Dear Reviewer,
    Thanks for your appreciation on our work. We will strive to research more effective methods to obtain better results. We have made further modifications to the manuscript, and our revisions are highlighted in red in the resubmitted manuscript. Please review.
Thanks again.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The authors have addressed my concerns carefully. The quality of the manuscript has been improved significantly. Therefore, I recommend acceptance of this manuscript.

Author Response

Dear Reviewer,

  Thank you very much for taking your time to review this manuscript. I really appreciate all your comments and suggestions! Please find my itemized responses in below, and my revisions are highlighted in red in the resubmitted manuscript.

Thanks again.

Response to Reviewer Comments

Point 1: Given the intentions of the authors, wouldn't it be clearer to revise the title of the paper as follows?.

Response 1: Thank you for your careful review and valuable suggestions. The title suggested by the reviewer can better convey the intentions of the manuscript. We have revised the title of the manuscript.

 

Point 2: Please explain the abbreviation of SMOTE..

Response 2: Thank you for your careful review and valuable suggestions. We have added the explaination of the abbreviation of SMOTE in Section 2.2.

 

Point 3: Please check that all references are relevant to the contents of the manuscript.

Response 3: Thank you for your careful review and valuable suggestions. We have checked all the references.

Author Response File: Author Response.docx

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