-->PONE-D-25-53239-->-->A new extended belief rule base method based on neighborhood covering reduction for diabetes diagnosis-->-->PLOS One

Dear Dr. He,

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.

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Academic Editor

PLOS One

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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.

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Reviewers' comments:

Reviewer's Responses to Questions

-->Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. -->

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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-->2. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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-->3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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-->4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.-->

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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-->5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)-->

Reviewer #1: The following points should be addressed to improve the clarity, rigor, and overall impact of the manuscript:

1.Data Description Inaccuracy (Section 4.1):

Comment: The text states, "The dataset comprises 1000 patients... with 844, 103, and 5 patients, respectively." This sums to 952, not 1000. Please verify and correct the total number of samples in the dataset to ensure accuracy.

2.Formula Numbering:

Comment: There is a duplication in equation numbering; two distinct equations are both labeled as "(7)". Please renumber all equations sequentially throughout the manuscript to avoid confusion.

3.Terminology Consistency:

Comment: The model name alternates between the full form "Extended Belief Rule Base" and the acronym "EBRB". For consistency and readability, it is recommended to use the acronym "EBRB" throughout the manuscript after it is first defined in the abstract or introduction.

4.Lack of Optimization Details (P-CMA-ES):

Comment: The description of the P-CMA-ES optimization process lacks critical implementation details, such as the termination criteria and population size. To enhance reproducibility, please specify all key hyperparameters used. Furthermore, providing a convergence curve of the optimization algorithm would help demonstrate that a stable solution was reached.

5.Need for Ablation Study:

Comment: The individual contributions of the NCR module and the P-CMA-ES optimization to the model's final performance are not evaluated. To disentangle their effects, it is strongly recommended to incorporate an ablation study. This should compare the performance of:

The pure EBRB model (without rule reduction).

The NCR-EBRB model (with rule reduction but without parameter optimization).

The full NCR-EBRB model (with both rule reduction and optimization).

This analysis is crucial for validating the necessity of each proposed component.

6.Missing Limitations Analysis:

Comment: The conclusion section would be strengthened by a discussion of the model's limitations. For instance, the performance appears sensitive to hyperparameters (e.g., the rule fusion threshold t). Furthermore, as hinted at in Table 3 with the 40% test set, rule reduction may lead to performance degradation when training data is scarce. Acknowledging these limitations provides a more balanced and scientifically honest perspective.

7.Strengthening the Conclusion:

Comment: The conclusion should more directly address the research objectives stated in the introduction. If "improving interpretability" was a key goal, the discussion should explicitly state how NCR-EBRB achieves this. For example, quantify the improvement by stating that the model "reduced the number of rules by 50% while maintaining 95% accuracy," thereby enhancing transparency and traceability.

Reviewer #2: 1. Formal theoretical justification for integrating NCR with EBRB is lacking

The manuscript introduces Neighborhood Covering Reduction (NCR) for EBRB rule reduction, yet the presentation remains largely algorithmic. A theoretical analysis of how this reduction affects the reasoning consistency or completeness of the EBRB system is absent. It is recommended that the authors include a discussion on topics such as rule coverage sufficiency, information preservation, or potential error bounds to strengthen the theoretical foundation.

2. Semantic consistency after rule reduction is not clearly addressed

In EBRB systems, rules encapsulate expert semantic knowledge, while NCR operates as a distance based rule selection method. The manuscript does not examine whether rule removal via NCR preserves the original semantic integrity of the expert knowledge. A discussion on the semantic preservation characteristics of the proposed NCR EBRB framework would therefore be valuable.

3. No automatic selection mechanism for the rule fusion threshold λ

Although Section 4.2 analyzes the influence of the rule fusion threshold λ, its determination in practice still depends on manual tuning. It is suggested that the authors consider validation based or adaptive strategies to automatically select an appropriate λ, thereby improving the usability and robustness of the method.

4. Worst case computational complexity of the rule reduction algorithm is not analyzed

Algorithm 1 employs a greedy forward search strategy; however, its worst case time and space complexity for large scale rule bases is not discussed. Providing a formal complexity analysis would help clarify the scalability of the proposed approach.

5. Identical Precision and Recall values require explanation

In Tables 3 and 5, Precision and Recall are repeatedly reported as equal. Such a result is uncommon in general classification tasks and warrants clarification—for instance, whether it stems from macro averaging, class imbalance, or specific implementation details.

6. Parameter settings of comparative models are not disclosed

The parameter configurations for the comparative models (SVM, KNN, Bagging Tree, and Boosting Tree) are not provided. This omission may compromise the fairness and reproducibility of the experimental comparisons. Reporting these details is essential for rigorous evaluation.

7. Section lengths are imbalanced

Section 3.2 is relatively lengthy compared to the concise Conclusion section. Rebalancing the manuscript structure would enhance overall readability and coherence.

8. Inconsistent figure/table numbering and textual references

Some figures and tables are inconsistently numbered or referenced in the main text. A thorough check to ensure consistency is recommended.

Reviewer #3: This manuscript proposes an extended belief rule base (EBRB) framework for diabetes diagnosis. The topic is relevant to clinical decision support, and the integration of rule-base reduction with an interpretable EBRB-style model is potentially useful. The paper is suitable for publication after minor revisions that address the following issues.

1. The manuscript states that NCR-EBRB outperforms other benchmark models across the four UCI datasets. However, Table 5 indicates that for Banknote, KNN (0.9075) exceeds NCR-EBRB (0.8929).

2. Equation (7) is used for the XGBoost gain function and later reused for the EBRB rule expression.

3. Algorithm 1 repeats step number “7” and has minor formatting issues.

4. Several visible typographical and spacing issues appear.

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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-->PONE-D-25-53239R1-->-->A new extended belief rule base method based on neighborhood covering reduction for diabetes diagnosis-->-->PLOS One

Dear Dr. He,

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 Apr 01 2026 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.. 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.

Please include the following items when submitting your revised manuscript:-->

• A 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 . 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,

Robin Haunschild

Academic Editor

PLOS One

Journal Requirements:

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.

Additional Editor Comments

Please update your submission files as you proposed.

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To ensure your figures meet our technical requirements, please review our figure guidelines: https://journals.plos.org/plosone/s/figures

You may also use PLOS’s free figure tool, NAAS, to help you prepare publication quality figures: https://journals.plos.org/plosone/s/figures#loc-tools-for-figure-preparation.

NAAS will assess whether your figures meet our technical requirements by comparing each figure against our figure specifications.

A new extended belief rule base method based on neighborhood covering reduction for diabetes diagnosis

PONE-D-25-53239R2

Dear Dr. He,

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.

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Kind regards,

Robin Haunschild

Academic Editor

PLOS One

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

-->Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.-->

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

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-->2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. -->

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

-->3. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: N/A

**********

-->4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

-->5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.-->

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

-->6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)-->

Reviewer #1: All comments have been revised, and the manuscript can be accepted. This paper has certain innovation and application prospects.

Reviewer #2: The authors have revised the manuscript according to the comments, and the quality has been improved significantly.

Reviewer #3: The authors have addressed all my comments. I have no further questions. I would recommend accepting this paper.

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-->7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.). 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 For information about this choice, including consent withdrawal, please see our Privacy Policy..-->

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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