Next Article in Journal
Magnetic Resonance Imaging Evaluation of Bone Metastases Treated with Radiotherapy in Palliative Intent: A Multicenter Prospective Study on Clinical and Instrumental Evaluation Assessment Concordance (MARTE Study)
Next Article in Special Issue
Thoracic Diseases: Technique and Applications of Dual-Energy CT
Previous Article in Journal
Faecal Immunochemical Testing to Detect Colorectal Cancer in Symptomatic Patients: A Diagnostic Accuracy Study
Previous Article in Special Issue
Multidetector CT Imaging Biomarkers as Predictors of Prognosis in Shock: Updates and Future Directions
 
 
Review
Peer-Review Record

Beyond Visual Interpretation: Quantitative Analysis and Artificial Intelligence in Interstitial Lung Disease Diagnosis “Expanding Horizons in Radiology”

Diagnostics 2023, 13(14), 2333; https://doi.org/10.3390/diagnostics13142333
by Gaetano Rea 1,*, Nicola Sverzellati 2, Marialuisa Bocchino 3, Roberta Lieto 1, Gianluca Milanese 2, Michele D’Alto 4, Giorgio Bocchini 1, Mauro Maniscalco 5, Tullio Valente 1 and Giacomo Sica 1
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Diagnostics 2023, 13(14), 2333; https://doi.org/10.3390/diagnostics13142333
Submission received: 18 June 2023 / Revised: 7 July 2023 / Accepted: 8 July 2023 / Published: 10 July 2023

Round 1

Reviewer 1 Report

Nice and concise review of AI in interstitial lung diseases. However, the authors should discuss with examples how machine learning and deep learning have enabled differentiation and prognostication of ILDs. The introduction ends abruptly. Please review and revise as appropriate. Challenges in practical implementation of these newer techniques should be addressed in greater details. The authors can refer to more recent articles on the subject for a comprehensive review. For example- Recent Advancements in Computed Tomography Assessment of Fibrotic Interstitial Lung Diseases - PubMed (nih.gov) and Artificial Intelligence and Interstitial Lung Disease: Diagnosis and Prognosis - PubMed (nih.gov)

The authors should review the manuscript for syntax and grammatical errors. Some sentences are very long, such as in the Introduction section lines 45 to 48 and lines 66-70. These should be made shorter for easy reading. Overall, the quality of English language is acceptable and easy to understand.

Author Response

The "point by point" responses to the reviewer have been provided in the attached word document. Thank You.

Author Response File: Author Response.docx

Reviewer 2 Report

Re: Beyond visual interpretation: Quantitative Analysis and Artificial Intelligence in Interstitial Lung Disease Diagnosis “Expanding Horizons in Radiology”

This review article reports the summary of quantitative analysis and AI in ILD diagnosis. It should be noted that this review does not introduce specific quantitative analysis technics in detail, but rather describes the current trend of quantitative analysis in abstract terms. Reviewer considers this a clear review article to understand the trend of quantitative analysis.

Minor revision

Please correct many mistakes in the manual when using abbreviations. For example, GGO (line237) from the first time is listed as an abbreviation, and GGO (line265) from the second time is listed with full spell. IPF is listed with full spell and as an abbreviation in two places. Some abbreviations are used for terms used only once in the text.

MDT and MDD are used interchangeably and the meaning of the text is different in some parts. Please correct.

Author Response

The "point by point responses to the reviewer have been provided in the attached word document. Thank You.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

1. Please remove the word team from line 57 as it is self-implied by MDT.

2. Please expand IPAD in line 62.

3. Please provide a citation for the study quoted in lines # 301-303.

Author Response

The requested considerations and corrections are attached in a word document for the reviewer's reference. Thank you

Author Response File: Author Response.docx

Back to TopTop