PONE-D-24-42415

Using Statistical Modelling and Machine Learning in Detecting Bone Properties: A Systematic Review Protocol

PLOS ONE

Dear Dr. Abdelhay,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we have decided that your manuscript does not meet our criteria for publication and must therefore be rejected.

Specifically:

the work presents a plan on how activities will be carried out to produce a review paper. Unfortunately, I do not believe this kind of study falls within the "Systematic reviews and meta-analyses" type of submission guidelines. 

In addition, the presented protocol turn out to have already been published on PROSPERO.

I am sorry that we cannot be more positive on this occasion, but hope that you appreciate the reasons for this decision.

Kind regards,

Alessandra Aldieri

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does the manuscript provide a valid rationale for the proposed study, with clearly identified and justified research questions?

The research question outlined is expected to address a valid academic problem or topic and contribute to the base of knowledge in the field.

Reviewer #1: Yes

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2. Is the protocol technically sound and planned in a manner that will lead to a meaningful outcome and allow testing the stated hypotheses?

The manuscript should describe the methods in sufficient detail to prevent undisclosed flexibility in the experimental procedure or analysis pipeline, including sufficient outcome-neutral conditions (e.g. necessary controls, absence of floor or ceiling effects) to test the proposed hypotheses and a statistical power analysis where applicable. As there may be aspects of the methodology and analysis which can only be refined once the work is undertaken, authors should outline potential assumptions and explicitly describe what aspects of the proposed analyses, if any, are exploratory.

Reviewer #1: Yes

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3. Is the methodology feasible and described in sufficient detail to allow the work to be replicable?

Descriptions of methods and materials in the protocol should be reported in sufficient detail for another researcher to reproduce all experiments and analyses. The protocol should describe the appropriate controls, sample size calculations, and replication needed to ensure that the data are robust and reproducible.

Reviewer #1: Yes

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4. Have the authors described where all data underlying the findings will be made available when the study is complete?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception, at the time of publication. 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: No

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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

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above and, if applicable, provide comments about issues authors must address before this protocol can be accepted for publication. You may also include additional comments for the author, including concerns about research or publication ethics.

You may also provide optional suggestions and comments to authors that they might find helpful in planning their study.

(Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1:  The subject of the proposed systematic review is the use of machine learning and artificial intelligence in general for the prediction of bone properties and subsequently fracture risk. It is indeed a very interesting research, but I think the journal should publish the review results, not just the protocol, that is already published on PROSPERO dedicated portal, anyway.

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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 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

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[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.]

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For journal use only: PONEDEC3

PONE-D-24-42415R1Using Statistical Modelling and Machine Learning in Detecting Bone Properties: A Systematic Review ProtocolPLOS ONE

Dear Dr. Abdelhay,

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 see the comments of the rewiwers bellow. 

Please submit your revised manuscript by February, 28. 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.

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We look forward to receiving your revised manuscript.

Kind regards,

Melissa Orlandin Premaor, M.D., Ph.D

Academic Editor

PLOS ONE

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Additional Editor Comments (if provided):

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does the manuscript provide a valid rationale for the proposed study, with clearly identified and justified research questions?

The research question outlined is expected to address a valid academic problem or topic and contribute to the base of knowledge in the field.

Reviewer #2: Yes

Reviewer #3: Yes

**********

2. Is the protocol technically sound and planned in a manner that will lead to a meaningful outcome and allow testing the stated hypotheses?

The manuscript should describe the methods in sufficient detail to prevent undisclosed flexibility in the experimental procedure or analysis pipeline, including sufficient outcome-neutral conditions (e.g. necessary controls, absence of floor or ceiling effects) to test the proposed hypotheses and a statistical power analysis where applicable. As there may be aspects of the methodology and analysis which can only be refined once the work is undertaken, authors should outline potential assumptions and explicitly describe what aspects of the proposed analyses, if any, are exploratory.

Reviewer #2: Yes

Reviewer #3: Partly

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3. Is the methodology feasible and described in sufficient detail to allow the work to be replicable?

Descriptions of methods and materials in the protocol should be reported in sufficient detail for another researcher to reproduce all experiments and analyses. The protocol should describe the appropriate controls, sample size calculations, and replication needed to ensure that the data are robust and reproducible.

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors described where all data underlying the findings will be made available when the study is complete?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception, at the time of publication. 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 #2: Yes

Reviewer #3: Yes

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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 #2: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above and, if applicable, provide comments about issues authors must address before this protocol can be accepted for publication. You may also include additional comments for the author, including concerns about research or publication ethics.

You may also provide optional suggestions and comments to authors that they might find helpful in planning their study.

(Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: 1. The manuscript tackles a critical and timely issue by exploring the application of AI and ML in detecting and predicting osteoporosis-related bone properties. This area of research is highly relevant, as traditional diagnostic methods like DXA face limitations in sensitivity and accessibility, leaving room for innovative technologies to make an impact.

2. The authors have presented a strong and methodologically rigorous protocol that adheres to PRISMA-P guidelines. Their use of established risk-of-bias tools, such as RoB 2 and QUADAS-2, ensures the reliability and transparency of the review. This approach enhances the credibility of the proposed study.

3. A notable strength is the interdisciplinary nature of the protocol, which incorporates a variety of AI/ML methods and data types, including imaging, genomic data, and wearable sensor data. This comprehensive scope allows for a broad understanding of AI/ML applications in osteoporosis detection and prediction.

4. However, the decision to include only English-language studies introduces potential language bias. Considering the global nature of osteoporosis research, this could exclude significant findings published in other languages. Addressing this limitation or providing a clear rationale for this choice would strengthen the manuscript.

5. While the authors acknowledge the challenge of rapidly evolving AI/ML technologies, the protocol does not outline a concrete strategy for updating the review with newly published studies. Including a plan to address this would ensure the review remains relevant and comprehensive over time.

6. The absence of illustrative examples or pilot data is a missed opportunity to provide readers with practical context. Even a hypothetical case or brief summary of existing AI/ML applications in osteoporosis could help clarify the practical implications of the study.

7. The discussion section could be expanded to better address the real-world impact of the review. For example, how could these findings influence clinical workflows, public health strategies, or the development of guidelines for integrating AI/ML into osteoporosis care?

8. While the manuscript is generally well-written and logically structured, some technical terms (e.g., ensemble methods, reinforcement learning) could be simplified or briefly explained to ensure accessibility for a broader audience, including clinicians and policymakers.

9. The authors’ commitment to making all data publicly available upon study completion aligns well with open science principles and enhances the transparency of the work. This is a commendable practice.

10. Overall, this protocol is well-conceived and has the potential to contribute significantly to the field. By addressing limitations such as language bias, providing practical examples, and elaborating on the broader implications of the findings, the manuscript could be further strengthened and have a more impactful reach.

Reviewer #3: Esteemed authors,

your proposal for SR and MA about this issue is meaningful and necessary; I would recommend, however, to narrow your inclusion criteria for adults over 60 years old; this recommendation, although it may limit the amount of studies available for review, it also may produce more meaningful results and avoid bias from analysing very different populations in the same MA. Another solution for this would be to analyse younger adults (< 60 YO) separately from older adults.

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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 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 #2: Yes:  Krit Pongpirul

Reviewer #3: No

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<p>Using Statistical Modelling and Machine Learning in Detecting Bone Properties: A Systematic Review Protocol

PONE-D-24-42415R2

Dear Dr. Abdelhay,

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,

Melissa Orlandin Premaor, M.D., Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments: