PONE-D-20-37399

BCDnet: Parallel Heterogeneous Eight-category Automatic Diagnosis Model of Breast Pathology

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.

As you will infer from below that there was a disagreement among the reviewers regarding enthusiasm for this work. Reviewer 1 was of the view that manuscript partly describes a technically sound piece of scientific research and recommended major revision. However,  Reviewer 2 was of the view that your work did not describe technically sound piece of scientific research and recommended reject. 

After thorough consideration of comments of reviewers, my decision is "major revision". Please incorporate comments raised by both reviewers. 

Please submit your revised manuscript by Apr 10 2021 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.

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We look forward to receiving your revised manuscript.

Kind regards,

Gulistan Raja

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: Partly

Reviewer #2: No

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

Reviewer #1: No

Reviewer #2: No

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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

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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: No

Reviewer #2: No

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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) The overall grammar and sentence framing in the paper are very weak, making the article quite unreadable. Grammar checks were not done at all.

2) The author should try to give data of the study region too, in the Introduction.

3) Example:

line 83… "Most of the research focuses on 84 relatively simple two classification"…. Here it appears that the author's research focuses on this.

Line 85… "…moving from two classifications….." maybe binary is a better term

Line 87…. "Improving the accuracy of the model by improving the data set has also been paid more and more attention". How has the data set been improved? Is this sentence part of literature, or this work?... is unclear.

Line 165… "If you load the weights and freeze all the convolutional layer weights, because the loaded weights come from the training of the ImageNet image set, the samples in the ImageNet image set have little correlation with the samples in the pathological tissue image set, so the experimental results of strategy 3 are poor." Very bad sentence framing.

Line 302… "…sample number distribution…." What does this mean?

4) Line 103…"….using random non-repetitive segmentation of the original image sample to enhance the data for the small sample can significantly improve the model performance". This sentence must have the support of citation.

5) Line 141… "Choose pre-trained models" Title should be appropriately named. Maybe Choice of pre-trained models.

6) It is not understood how Figure 2 describes the model structure. Further, no description is added of the labels in the figure.

7) Table 2 mentions the raw dataset numbers. There is no breakup of what the enhanced dataset numbers are.

8) Line 295… "…The abscissa is the xx patien…” What is this xx?

9) The paper has commas and blanks spaced out at will. Seems like a very hurriedly written paper.

10) The paper's only novelty is the 8-class classification, which is interesting, and hence carries a chance for re-submission.

11) But, if a new AI method/theory is being reported in the paper, it should be compared and validated against at least one other common data set (bench mark datasets) for which a published study exists using at least one other method/approach, and preferably a method/approach which has been widely used in the field.

12) Also, baselines are not strong (e.g., did not compare with state-of-the-art approaches)

Reviewer #2: In this manuscript, the authors clearly define their problem – there are tons of studies that do benign/normal binary classification but few that address the need to be able to distinguish between different kinds of lesions.

They fuse two pretrained CNNs by concatenating their output features and retrain a subset of layers in order to classify small histopathological images into one of eight categories. They test the performance of their model at different magnifications and with/without using data augmentation.

Overall, the manuscript is difficult to follow mainly to do deviance from structural conventions and lack of organization. There are also experimental details which are unclear or left out which yields the work unreproducible.

My comments are below.

Major

Generally, research articles are structured with abstract, introduction, methods, results, discussions, and conclusion headings. Can the authors reorganize their manuscript according to these conventions?

Though some ideas presented by the authors can be understood, some paragraphs are difficult to understand. For example, this reviewer finds it difficult to understand what is being said on lines 101-109. There are also numerous instances of sentence fragments, run-on sentences, comma splices, etc. Please have someone who is fluent in English to proof read the manuscript.

It is not clear in the "Choose pre-trained models" subsection how models are trained nor what results are reported in Table 1. The authors state that they are using strategies 2, 3, and 4 to pre-train on a small set of pathological tissues. What performance metric is being measured? Accuracy? How are large tissue images being processed by the fixed-input CNNs? Can the authors describe the distribution of the dataset before presenting results?

The authors do well describing Resnet50 and VGG16. This reviewer can understand that the 30th and 10th layers respectively are frozen as well as preceding layers. Then, deep layers are retrained. However, it is not clear what parameters are utilized to fine-tune these networks (learning rate, optimizer, weight biases, etc.). Furthermore, it is not clear what is the 30th layer or 10th layer of these networks. Generally when describing CNN layers, we prefer to refer to abstracted components of the network. For example, Resnet50 has five residual "blocks." It would help to clarify these sections.

The resampling strategy proposed by the authors to combat class imbalances is well-founded. However, the description provided is not clear enough to reproduce the resampling strategy. Can the authors rephrase their description?

The authors make it a point that class imbalance will be an issue, but given the results, it seems as if it hardly makes a difference. Yes, the majority of performance metrics are higher with augmentation but only a little bit. Can the authors provide some discussion on this?

Minor

It is a bit unusual to compare lung and breast cancer as a race to first place on lines 40-41 on page 2. Please rephrase.

The transition from pathological diagnosis to image classification on lines 46-47 on page 2 is non-sequitur. Please rephrase.

What does "pre-screened" mean on line 233 page 7?

What is meant by "mark" in Table 3 (page 10)?

What is verification accuracy and loss?

Can the authors represent Table 4 as a grouped bar graph? It is difficult to see the differences in performance with such a large table.

One of the columns for Dataset400X in Table 4 contain results rather than marks. Please fix.

Does Table 4 report cross-validation metrics?

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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.]

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Attachments

Attachment

Submitted filename: PONE-D-20-37399 REVIEW COMMENTS.docx

PONE-D-20-37399R1

BCDnet: Parallel heterogeneous eight-class classification model of breast pathology

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.

Specifically, the English language should be improved further.

Please submit your revised manuscript by Jul 17 2021 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: http://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,

Gulistan Raja

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided): English language should be improved further

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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: 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 #2: Yes

Reviewer #3: No

Reviewer #4: Yes

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

Reviewer #2: N/A

Reviewer #3: No

Reviewer #4: 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.

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: 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 #2: Yes

Reviewer #3: No

Reviewer #4: 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 #2: The authors have done a very good job while revising the manuscript; however, a couple of my comments were overlooked or not properly addressed. Looking at the amount of effort the authors have put in revising the manuscript, I recommend this publication for publication.

Reviewer #3: This is the review of the paper titled " BCDnet: Parallel heterogeneous eight-class classification model of breast pathology"

The paper has many flaws which I will list some of them.

1- poor novelty, there is nothing new in the paper.

2- poor presentation, many sentences are ambiguous.

3- the used dataset is old and very high results achieved on the dataset.

4- no confusion matrics are presented and visualization of the learned filters.

5- Poor English

This paper is not in the level of PLOS One journal, I would suggest submitting it to a different journal.

Reviewer #4: This paper can be accepted since the authors have revised it according to the comments of the reviewers.

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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: No

Reviewer #4: 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.

BCDnet: Parallel heterogeneous eight-class classification model of breast pathology

PONE-D-20-37399R2

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,

Gulistan Raja

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments: