Comparison of Monkeypox and Wart DNA Sequences with Deep Learning Model

Round 1

Reviewer 1 Report

1)      Authors should add motivation and contribution in the introduction section

2)      Author should make one table in related study with existing work and their limitations?

3)      How the proposed model is beneficial in decentralized system?

4)      All the table must be improved and the text within the table must be aligned properly.

5)      The grammar and typos error must be taken care 

6)      Author should add advantages and disadvantages of the proposed model.

7) Is the proposed system secure enough and sutainable to apply in distributed environment. If yes, kindly approach with the below work and preferably include in the realted work

a) Kumar, R., & Tripathi, R. (2020, November). A Secure and Distributed Framework for sharing COVID-19 patient Reports using Consortium Blockchain and IPFS. In 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC) (pp. 231-236). IEEE.

Author Response

Dear reviewer,

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report

·        The work is of limited novelty. It is not technically challenging.

·        The proposed method lacks motivation and justifications. More advantages should be discussed in detail,

·        The paper contains a number of grammatical errors and can be better organized with more definitions.

·        In introduction, the authors take several paragraphs to introduce the background while they are not very relevant to the task of age prediction.

·        References must be updated and it seems that authors need to refer to latest work to justify the current approach

·        The technical quality of this paper is quite low. Although theoretical concepts and related literature are properly introduced, some of the references are outdated and should be omitted. Moreover, the number of recent literature is low

·        I recommend authors present some papers to show briefly different methods and their feasibility to apply to the studied subject. This can make reader to extend his/her view about the importance of your job. need more convinced literature reviews to indicate clearly the state-of-the-art development. Consider the following studies in the reference section:

1.         Optimization of neural network using improved bat algorithm for data classification

2.         Analyzing RNA-seq gene expression data using deep learning approaches for cancer classification

·        The novelty is limited. What is the contribution of this paper from the modeling perspective? 

·        The aim/objective of the paper is not mentioned in the Introduction section, a brief discussion required

Author Response

Dear reviewer,

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

All changes are incorporated by author