All reviews of published articles are made public. This includes manuscript files, peer review comments, author rebuttals and revised materials. Note: This was optional for articles submitted before 13 February 2023.
Peer reviewers are encouraged (but not required) to provide their names to the authors when submitting their peer review. If they agree to provide their name, then their personal profile page will reflect a public acknowledgment that they performed a review (even if the article is rejected). If the article is accepted, then reviewers who provided their name will be associated with the article itself.
Author has addressed reviewer comments properly. Thus I recommend publication of the manuscript.
[# PeerJ Staff Note - this decision was reviewed and approved by Xiangjie Kong, a PeerJ Section Editor covering this Section #]
Please read the author guidelines and double check the references and revise the manuscript as per the reviewer suggestions and resubmit it.
No Comment
No Comments
no comments
no comments
Good
Good
Good
The authors have addressed most of the comments. However, the references are not complete. Information is missing in multiple references that must be corrected.
I am happy to announce that review of your manuscript is now complete. Kindly revise the manuscript as per the reviewer suggestions and resubmit it.
**PeerJ Staff Note:** Please ensure that all review and editorial comments are addressed in a response letter and that any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate.
**Language Note:** The review process has identified that the English language must be improved. PeerJ can provide language editing services - please contact us at [email protected] for pricing (be sure to provide your manuscript number and title). Alternatively, you should make your own arrangements to improve the language quality and provide details in your response letter. – PeerJ Staff
No comments
Work is good. But the justification of ensemble models is necessary.
Please explain for which cause, the results are good. Please add which parameter is responsible for it.
Good work. Please have a look on grammar. Recent papers may be included in references. On ensemble some of the work of A. Das et. al. with medical images. Please have a look on these if may need to refer for comparison.
In this work, the authors have proposed an ensemble learning framework for early detection of breast cancer from the given image and validated the proposed framework on different publically available datasets. However, the pseudocode of the proposed framework is not well written.
The authors have evaluated the performance of four different deep-learning pre-trained models to build their ensemble model. However,
1. The authors have not mentioned how these models have been selected and why their study has not considered other deep-learning models.
2. It is also not mentioned clearly, how the models' predictions combined to create the resultant ensemble.
No Comment
The introduction section is not well written. It should be rewritten by clearly addressing the following questions:
What?
Why (Motivation or importance of study)? and
How (Major contribution)?
The author may cite the article "Jakhar, Amit Kumar, Aman Gupta, and Mrityunjay Singh. "SELF: a stacked-based ensemble learning framework for breast cancer classification." Evolutionary Intelligence (2023): 1-16." in their study.
**PeerJ Staff Note:** It is PeerJ policy that additional references suggested during the peer-review process should only be included if the authors agree that they are relevant and useful.
All text and materials provided via this peer-review history page are made available under a Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.