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Applied Sciences
Volume 12
Issue 21
10.3390/app122110760
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Article
Peer-Review Record

An Efficient Strategy for Blood Diseases Detection Based on Grey Wolf Optimization as Feature Selection and Machine Learning Techniques

Appl. Sci. 2022, 12(21), 10760; https://doi.org/10.3390/app122110760
by Nada M. Sallam 1,2,*, Ahmed I. Saleh 2, H. Arafat Ali 2,3 and Mohamed M. Abdelsalam 2
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Appl. Sci. 2022, 12(21), 10760; https://doi.org/10.3390/app122110760
Submission received: 20 September 2022 / Revised: 24 September 2022 / Accepted: 27 September 2022 / Published: 24 October 2022

Round 1

Reviewer 1 Report

The paper describes using AI to differentiate malignant and benign tumors in leukemia. Overall the paper is very clear and ready for publication. Figure 8 has unreadable boxes in the pdf I reviewed. The English has room for improvement.

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 2 Report

1. Some errors

Title  -> Remove the last '.'

The font sizes of Eqs.(10) - (12) are inconsistent.

Fig. 8 shows erros

 

2. What is the number of features after feature extraction?

What is the number of features after feature selection?

 

3. using World Health Organization (WHO) or

The full name of WHO only needs to be written when it first appears.

 

4. In the Related studies, the authors should introdouce the works of GWO, such as:

Improved binary grey wolf optimizer and its application for feature selection

P Hu, JS Pan, SC Chu

Knowledge-Based Systems 195, 105746

 

New hybrid algorithms for prediction of daily load of power network

P Hu, JS Pan, SC Chu, QW Chai, T Liu, ZC Li

Applied Sciences 9 (21), 4514

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 3 Report

1.      How will your study benefit future researchers?

2.      What are the limitations of your study?

3.      A section for the assumption is also required to show what authors assume to develop this manuscript.

4.      Extensive English corrections are required for better understanding.

5.      Flowchart fig 8 needs to be redrawn with proper explanation.

6.      Literature survey needs improvement. Authors must add latest research as mentioned below:

a)      Fuzzy-Based Shunt VAR Source Placement and Sizing by Oppositional Crow Search Algorithm

b)      Voltage constrained reactive power planning problem for reactive loading variation using hybrid harris hawk particle swarm optimizer

c)      Optimal placement of TCSC and SVC for reactive power planning using Whale optimization algorithmComputational complexity is an important factor in any optimization algorithm, the authors must provide the same for proposed algorithm with respect to the original algorithm.

7.      Theoretical justification about the effect of modification on the proposed algorithm

 

should be added.

Author Response

Please see the attachment

Author Response File: Author Response.docx

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