PONE-D-23-25069Classifier Machine Learning Algorithm for Ventilator Mode Selection, Pressure and Volume ControlPLOS ONE

Dear Dr. Thilakar,

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Praveen Kumar Donta, Ph.D.

Academic Editor

PLOS ONE

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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: N/A

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.

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: 1. Author need to synchronize the usage of the classifier terms in this research similar to the term written in Fig 3.

2. Author need to further elaborate the steps/activities involves in the classifier framework (fig 4) and relate with the discussion in line 205.

3. Please modify the section number in the summarization of introduction (end paragraph of introduction section) accordingly.

4. Please write/refer to the exact figure no and table no and not general statement of figure and number (e.g line 341)

Reviewer #2: 1. Hyperparameters need to be mentioned for ML classifiers.

2. Whether 5 fold or 10 fold validation performed?

3.Image quality need to be improved.

4. Contributions should have crisp points.'

5. Fig 5 is general...hence can be removed.

6. Discussion of proposed work results with existing literature works needs to be improved.

Reviewer #3: The article is well written in terms of problem specifications, modeling, and results according to the different machine learning algorithms. The article is also suitable in terms of scientific contributions.

Only thing which I have noticed to be rectified in Figures, 12, 13, 17 and 18 for term 'Decision Trees'. Which has to be corrected. Else is fine.

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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PONE-D-23-25069R1Classifier Machine Learning Algorithm for Ventilator Mode Selection, Pressure and Volume ControlPLOS ONE

Dear Dr. Thilakar,

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 Jan 22 2024 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.

Please include the following items when submitting your revised manuscript:

• 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,

Praveen Kumar Donta, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments:

Please consider reviewers comments carefully and resubmit the paper with em or ugh improvements.

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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 #2: All comments have been addressed

Reviewer #3: All comments have been addressed

Reviewer #4: (No Response)

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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 #2: Yes

Reviewer #3: Yes

Reviewer #4: No

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

Reviewer #2: N/A

Reviewer #3: Yes

Reviewer #4: No

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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.

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: 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

Reviewer #4: No

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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 #2: The authors have addressed all the comments given by the reviewers . Hence the article can be accepted in this current form.

Reviewer #3: In the article, "Classifier Machine Learning Algorithm for Ventilator Mode Selection, Pressure and

Volume Control" authors have addressed all the review queries. Now, I recommend the article for acceptance.

Reviewer #4: The paper proposes the existing ML techniques for the Ventilator Mode Selection. A simulation was developed to validate the proposed framework. However, there are many issues about this work. It is hard to follow, and the contribution is unclear.

In its current form, the paper only shows a more or less trivial approach. A better description of the novelty of this work is required right from the introduction. Furthermore, considering the current advances on ML, it becomes hard to understand the interest in this topic. In my opinion, the authors should take some efforts for convincing the reader of the interest and validity of their approach.

Authors need to deeply review both grammar and the organization of the paper. Generally speaking, the paper has many grammatical issues with several sentences hard to comprehend. Thus, it cannot be accepted without profound proof-reading. I recommend a whole paper revision by a native English speaker.

Other Comments:

In the title -> "Classifier Machine Learning Algorithm": "Classifier" and "Machine Learning Algorithm" are both terminologies used interchangeably in the research. Both are nouns, and therefore, the title is vague and does not clearly represent the content.

The abstract must present results for other classifiers that have been tested alongside NN.

The word "best" is used to indicate better performance in the article. I believe nothing is the best; however, when comparing techniques, we can talk about "better" performance of one technique over another.

The contribution listed in Line# 104 states a significant contribution. This is a very strong statement. I suggest the authors clearly articulate the contribution and provide statistical proof for general scenarios when using the term "significant."

Line 125: How can authors say "most frequently"? Is there any supporting data? Furthermore, in the next line, authors have selected CPAP and PAV modes but give no justification for choosing these among a number of existing modes.

Line 515: Using "significantly" implies that the facts are generally proven using statistical techniques. Otherwise, very strong justification would be required to claim that it gives the same results in all cases.

The authors need to familiarize themselves with terms like Classifier, Classifier Algorithm, Machine Learning Algorithm, etc. and then check the write-up against the terminologies used.

Section 3.3: I could not get a clear picture of this section. The explanation, the storyline, the organization, and the relevance with Fig 4. There is no clear flow of explanation given.

Table 3 and Table 4: We need to understand why one technique performs better and why the other performs poorly. It is not just about translating facts and figures into text.

Overall, it seems that the concept of ML techniques is weakly presented in the article. Starting from the ML background study, then the selection of techniques, implementation (experimental setup), and ending with experimental analysis—all these phases lack strong storylines and knowledge.

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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: No

Reviewer #3: Yes: Dr. Sanjiv Kumar Jain

Reviewer #4: 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.]

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.

Machine Learning Algorithm for Ventilator Mode Selection, Pressure and Volume Control

PONE-D-23-25069R2

Dear Dr. Thilakar,

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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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,

Praveen Kumar Donta, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

No further comments.

Reviewers' comments: