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Volume 7
Issue 7
10.3390/data7070095
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Data Descriptor
Peer-Review Record

Annotations of Lung Abnormalities in the Shenzhen Chest X-ray Dataset for Computer-Aided Screening of Pulmonary Diseases

Data 2022, 7(7), 95; https://doi.org/10.3390/data7070095
by Feng Yang 1,*,†, Pu Xuan Lu 2,†, Min Deng 3, Yì Xiáng J. Wáng 3, Sivaramakrishnan Rajaraman 1, Zhiyun Xue 1, Les R. Folio 4, Sameer K. Antani 1,* and Stefan Jaeger 1,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3:
Laith Alzubaidi
Data 2022, 7(7), 95; https://doi.org/10.3390/data7070095
Submission received: 20 May 2022 / Revised: 8 July 2022 / Accepted: 8 July 2022 / Published: 13 July 2022
(This article belongs to the Section Computational Biology, Bioinformatics, and Biomedical Data Science)

Round 1

Reviewer 1 Report

The article is sound and well organized. I still have a problem here: given that this is a data publication, I am not sure I can be happy without seeing the data. I suggest the authors to provide at least a private link for the review process.

Minor: please verify that each acronym is explained at its first appearance (see for instance TB in the abstract)

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

The manuscript described authors' work on collecting and annotating lung abnormalities for TB patients on pixel level (fine-grained) for the Shenzhen chest X-ray dataset which was previously made publicly available by the U.S. National Library of Medicine and No. 3. People’s Hospital Shenzhen, China. The annotations described in the manuscript were collected in collaboration with radiologists at the Chinese University of Hong Kong and will be publicly accessible on github.

The article is concise and well written. Examples of the annotations are provided. The dataset annotations could be helpful for future pulmonary diseases classification related research.

The main criticism would be:

The work is mainly about data manual modeling, which is short on innovation and novelty.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

I appreciate the dataset that you collected and wish to have the following 

1- More details about the annotation process, is there an expert with a medical background. 

2- if possible, increase the dataset, still very small for deep learning models. 

3- is it possible to prepare the same dataset for classification tasks with balanced classes. 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

the link of the dataset is working now, please proceed with process.

Author Response

Thanks for the reviewer's reply. Since the reviewer has no additional comments, we are not providing a point-by-point response.

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