Adaptive federated clustering for uncertainty-aware learning on decentralized big data platforms

Mohsen H. Alhazmi

doi:10.1371/journal.pone.0337069

Peer Review History

Original SubmissionAugust 12, 2025
15 Sep 2025 Decision Letter - Abdul Ahad, Editor Dear Dr. Alhazmi, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Oct 30 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols . We look forward to receiving your revised manuscript. Kind regards, Abdul Ahad, PhD Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Please note that PLOS One has specific guidelines on code sharing for submissions in which author-generated code underpins the findings in the manuscript. In these cases, we expect all author-generated code to be made available without restrictions upon publication of the work. Please review our guidelines at https://journals.plos.org/plosone/s/materials-and-software-sharing#loc-sharing-code and ensure that your code is shared in a way that follows best practice and facilitates reproducibility and reuse. 3. In the online submission form, you indicated that “The datasets generated and analyzed during this study will be made available by the corresponding author upon reasonable request.” All PLOS journals now require all data underlying the findings described in their manuscript to be freely available to other researchers, either 1. In a public repository, 2. Within the manuscript itself, or 3. Uploaded as supplementary information. This policy applies to all data except where public deposition would breach compliance with the protocol approved by your research ethics board. If your data cannot be made publicly available for ethical or legal reasons (e.g., public availability would compromise patient privacy), please explain your reasons on resubmission and your exemption request will be escalated for approval. 4. Please ensure that you refer to Figure 115 in your text as, if accepted, production will need this reference to link the reader to the figure. 5. Please include a copy of Table 13 which you refer to in your text on page 31 in PDF submission. 6. We note you have included a table to which you do not refer in the text of your manuscript. Please ensure that you refer to Table 23 in your text; if accepted, production will need this reference to link the reader to the Table. 7. If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? Reviewer #1: Yes Reviewer #2: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? -->?> Reviewer #1: Yes Reviewer #2: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available??> The PLOS Data policy Reviewer #1: Yes Reviewer #2: No ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English??> Reviewer #1: Yes Reviewer #2: No ****** Reviewer #1: The paper is with the title "Adaptive Federated Clustering for Uncertainty-Aware Learning on Decentralized Big Data Platforms" is highly related and well written. However it is advised to align the problem statement and the objectives. It is strongly advised to add the latest references for each of the problem statements. For example the problem statement one is referring to inadequate approaches for large-scale, decentralized big data. It would be more verifiable if comes with a few latest references. Also make sure the objective one addressing the first problem statement. The objective two addressing the second problem statement and so on. Reviewer #2: The abstract is written in a very general way and does not provide enough detail. It also lacks clear evidence and results to show the real importance of the work. Adding more technical explanation, presenting solid results, and mentioning possible limitations would make the abstract stronger. The paper covers an interesting topic but has many grammar and writing style problems. These issues affect readability. For example, in one sentence an extra number “53” appeared by mistake, and the phrase could be written more smoothly. The authors should carefully correct grammar and remove such errors to improve clarity. The paper discusses a relevant issue, but the problem statement and research objectives are not clearly explained. The contributions of the study should also be highlighted more directly. The introduction and overall structure need better organization to improve the flow of ideas. There are also several grammar and typo errors. With clearer writing and better structure, the paper has strong potential. The experiments are incomplete because important benchmark datasets like CIFAR-10, CIFAR-100, and Fashion-MNIST are missing. These are standard datasets in the field and should be included to test the method properly. In addition, the results are not compared with existing state-of-the-art methods. Without these comparisons, it is hard to judge the true performance. The paper would be stronger if it included experiments with these datasets and provided comparisons with baseline methods. The paper uses the term “vague system boundaries” but does not explain it clearly. Readers do not know what these boundaries mean in the context of federated learning. The authors should explain whether it relates to differences between clients, the scope of data, or something else. A clear explanation would help readers understand the challenges and how AFC deals with them. The paper introduces the AFC framework but the introduction section has many issues. The structure is unclear, and there is no roadmap to guide the reader. Subheadings appear suddenly and disrupt the flow, while too much technical detail is placed too early in the paper. The problem statement is scattered and unclear, and the AFC framework is introduced too late, making the contribution less visible. The motivation for AFC is also not strong enough, as the introduction does not show why AFC is needed compared to existing research. Transitions between sections are abrupt, and the objectives and contributions are not clearly linked to the challenges. The introduction should be reorganized so that the challenges flow smoothly into the problem statement, followed by the proposed AFC framework. The objectives should be listed clearly, and the novelty of AFC should be emphasized. There are also minor issues such as grammar errors, awkward sentences, and too much technical detail in the introduction that should be moved to the related work section. The paper also does not discuss any limitations of AFC, which would help present a more balanced perspective. Overall, the paper has promise, but the introduction needs major revision to improve clarity, structure, and motivation. Figure 2 does not clearly show the concept of adaptive federated clustering and selection. The labeling is confusing and the arrows are repetitive. The explanation in the methodology section also does not clarify the figure well. Both the figure and the related text should be revised for better understanding. The dataset section is weak because it does not explain why the chosen dataset, MIMIC-III, was selected. The connection between the dataset and the main concept of the paper is not clear. The authors should explain how the dataset relates to the study and why it is suitable. ****** what does this mean? ). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy Reviewer #1: No Reviewer #2: No ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0337069.r001
Revision 1
25 Sep 2025 Author Response Rebuttal Report Reviewer #1 Comments Comment 1: However, it is advised to align the problem statement and the objectives. Response: I have revised Section 1.2 Problem Definition and Objectives to ensure that each problem statement directly maps to a corresponding objective. Comment 2: It is strongly advised to add the latest references for each of the problem statements. For example, the problem statement one is referring to inadequate approaches for large-scale, decentralized big data. It would be more verifiable if comes with a few latest references. Response: Latest references from 2022–2024 have been added in the Problem Definition section to support each identified problem. Comment 3: Also make sure the objective one addressing the first problem statement. The objective two addressing the second problem statement and so on. Response: The objectives have been reordered and rewritten so that each directly addresses its corresponding problem statement in Section 1.2. Reviewer #2 Comments Comment 1: The abstract is written in a very general way and does not provide enough detail. It also lacks clear evidence and results to show the real importance of the work. Adding more technical explanation, presenting solid results, and mentioning possible limitations would make the abstract stronger. Response: The Abstract has been revised to include technical details, quantitative results, and a brief note on limitations. Comment 2: The paper covers an interesting topic but has many grammar and writing style problems. These issues affect readability. For example, in one sentence an extra number “53” appeared by mistake, and the phrase could be written more smoothly. The authors should carefully correct grammar and remove such errors to improve clarity. Response: The manuscript has been carefully proofread. Grammar issues, typos, and stylistic errors (including the extra “53”) have been corrected throughout the document. Comment 3: The paper discusses a relevant issue, but the problem statement and research objectives are not clearly explained. The contributions of the study should also be highlighted more directly. The introduction and overall structure need better organization to improve the flow of ideas. There are also several grammar and typo errors. With clearer writing and better structure, the paper has strong potential. Response: I revised the Introduction for better organization, clarified the Problem Definition, aligned the Objectives, and explicitly highlighted the Contributions. Grammar and typographical errors were also corrected. Comment 4: The experiments are incomplete because important benchmark datasets like CIFAR-10, CIFAR-100, and Fashion-MNIST are missing. These are standard datasets in the field and should be included to test the method properly. In addition, the results are not compared with existing state-of-the-art methods. Without these comparisons, it is hard to judge the true performance. The paper would be stronger if it included experiments with these datasets and provided comparisons with baseline methods. Response: I expanded the Experimental Section by adding results on CIFAR-10, CIFAR-100, and Fashion-MNIST. Comparisons with FedAvg, FedProx, FedYogi, FedAdapt, FedFormer, and HAFED have also been included. Comment 5: The paper uses the term “vague system boundaries” but does not explain it clearly. Readers do not know what these boundaries mean in the context of federated learning. The authors should explain whether it relates to differences between clients, the scope of data, or something else. A clear explanation would help readers understand the challenges and how AFC deals with them. Response: I expanded Section 1.2 Problem Definition and the related discussion to clarify vague system boundaries. The explanation now covers client roles, participation stability, and data ownership, with healthcare and IoT examples. Comment 6: The paper introduces the AFC framework but the introduction section has many issues. The structure is unclear, and there is no roadmap to guide the reader. Subheadings appear suddenly and disrupt the flow, while too much technical detail is placed too early in the paper. The problem statement is scattered and unclear, and the AFC framework is introduced too late, making the contribution less visible. Response: I reorganized the Introduction. A clear roadmap is now provided. Technical details were shifted to the Methodology, while the Problem Statement and Objectives are presented in a structured manner. Comment 7: The motivation for AFC is also not strong enough, as the introduction does not show why AFC is needed compared to existing research. Transitions between sections are abrupt, and the objectives and contributions are not clearly linked to the challenges. The introduction should be reorganized so that the challenges flow smoothly into the problem statement, followed by the proposed AFC framework. The objectives should be listed clearly, and the novelty of AFC should be emphasized. Response: The Introduction has been rewritten to strengthen motivation. Section flow was improved so that challenges lead directly into the problem statement, objectives, and then the AFC framework. The novelty of AFC is emphasized with explicit comparisons to prior work. Comment 8: There are also minor issues such as grammar errors, awkward sentences, and too much technical detail in the introduction that should be moved to the related work section. The paper also does not discuss any limitations of AFC, which would help present a more balanced perspective. Overall, the paper has promise, but the introduction needs major revision to improve clarity, structure, and motivation. Response: I corrected grammar and sentence structure issues, moved technical details from the Introduction to Related Work, and added a Limitations and Future Work section. Comment 9: Figure 2 does not clearly show the concept of adaptive federated clustering and selection. The labeling is confusing and the arrows are repetitive. The explanation in the methodology section also does not clarify the figure well. Both the figure and the related text should be revised for better understanding. Response: Figure 2 has been redesigned with clearer labels and simplified arrows. The explanation in the Methodology Section was rewritten to align directly with the figure. Comment 10: The dataset section is weak because it does not explain why the chosen dataset, MIMIC-III, was selected. The connection between the dataset and the main concept of the paper is not clear. The authors should explain how the dataset relates to the study and why it is suitable. Response: I expanded the Dataset Section to justify the selection of MIMIC-III. The description now explains its relevance to healthcare, decentralized silos, and privacy-preserving FL scenarios. Summary: I sincerely thank the reviewers for their detailed and constructive feedback. All comments were carefully addressed through major revisions, including structural improvements, grammar corrections, expanded experimental evaluation, clarification of vague concepts, and stronger motivation. I believe the revised manuscript is now significantly improved in clarity, technical depth, and alignment with the journal’s standards. Attachments Attachment Submitted filename: V2-Response File.docx https://doi.org/10.1371/journal.pone.0337069.r002
5 Nov 2025 Decision Letter - Abdul Ahad, Editor Adaptive Federated Clustering for Uncertainty-Aware Learning on Decentralized Big Data Platforms PONE-D-25-43938R1 Dear Dr. Alhazmi, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. For questions related to billing, please contact billing support . If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Abdul Ahad, PhD Academic Editor PLOS ONE Reviewers' comments: Reviewer's Responses to Questions Comments to the Author Reviewer #1: All comments have been addressed Reviewer #2: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions??> Reviewer #1: Yes Reviewer #2: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? -->?> Reviewer #1: Yes Reviewer #2: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available??> The PLOS Data policy Reviewer #1: Yes Reviewer #2: No ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English??> Reviewer #1: Yes Reviewer #2: Yes ****** Reviewer #1: The authors have incorporated all the comments and no further feedback is required. Authors are always welcomed to further proofread their manuscript before publication. Reviewer #2: (No Response) ****** what does this mean? ). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy Reviewer #1: Yes Reviewer #2: No ******** https://doi.org/10.1371/journal.pone.0337069.r003
Formally Accepted
Acceptance Letter - Abdul Ahad, Editor PONE-D-25-43938R1 PLOS ONE Dear Dr. Alhazmi, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. You will receive an invoice from PLOS for your publication fee after your manuscript has reached the completed accept phase. If you receive an email requesting payment before acceptance or for any other service, this may be a phishing scheme. Learn how to identify phishing emails and protect your accounts at https://explore.plos.org/phishing. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Abdul Ahad Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0337069.r004

Open letter on the publication of peer review reports

PLOS recognizes the benefits of transparency in the peer review process. Therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. Reviewers remain anonymous, unless they choose to reveal their names.

We encourage other journals to join us in this initiative. We hope that our action inspires the community, including researchers, research funders, and research institutions, to recognize the benefits of published peer review reports for all parts of the research system.

Learn more at ASAPbio .