Next Article in Journal
Identification and Characterization of the HbPP2C Gene Family and Its Expression in Response to Biotic and Abiotic Stresses in Rubber Tree
Previous Article in Journal
Regulation of NAD+/NADH Redox Involves the Protective Effects of Ginsenoside Rb1 against Oxygen–Glucose Deprivation/Reoxygenation-Induced Astrocyte Lesions
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 24
Issue 22
10.3390/ijms242216060
Review Report
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
Article
Peer-Review Record

Machine Learning Quantification of Intraepithelial Tumor-Infiltrating Lymphocytes as a Significant Prognostic Factor in High-Grade Serous Ovarian Carcinomas

Int. J. Mol. Sci. 2023, 24(22), 16060; https://doi.org/10.3390/ijms242216060
by Jesús Machuca-Aguado 1, Antonio Félix Conde-Martín 1, Alejandro Alvarez-Muñoz 1, Enrique Rodríguez-Zarco 1, Alfredo Polo-Velasco 2, Antonio Rueda-Ramos 3, Rosa Rendón-García 1, Juan José Ríos-Martin 1 and Miguel A. Idoate 1,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Int. J. Mol. Sci. 2023, 24(22), 16060; https://doi.org/10.3390/ijms242216060
Submission received: 11 October 2023 / Revised: 26 October 2023 / Accepted: 1 November 2023 / Published: 7 November 2023
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The present Article, ijms-2685419, entitled: (MACHINE LEARNING QUANTIFICATION OF INTRAEPI-THELIAL TUMOR-INFILTRATING LYMPHOCYTES AS A SIGNIFICANT PROGNOSTIC FACTOR IN HIGH-GRADE SEROUS OVARIAN CARCINOMAS)

The Research article is very informative and written in a very concise way. However, I have the following minor comments:

-        -  p value need to be italic along the whole manuscript.

-          -Numbers below figures (2-4) cannot be seen.

-      -Authors need to follow journal format to quite references inside text and in the journal list.

-         - Is it possible to state the precision % of the applied method???

Comments on the Quality of English Language

Minor editing of English language required

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript is very interesting but presents some points that must be improved. Figures must be improved while tables are clear. My comments are listed below: 

Introduction: It deserves to be pointed out that ovarian cancer recurrence is mainly due to the occurrence of chemotherapy resistance. In fact, cancer cells show an increased antioxidant responce (see PMID: 37175546 ) allowing a protection from platinum-derived drugs.

Figure 2 and 3: Images quality is very low and must be improved

Figures: remove the figure number (e.g. "Figure 1" from the image since it is already written in the legend

A table with the clinico-demographic characteristics of patients must be added

An accurate revision of typing errors is recommended

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

the manuscript has been significantly improved and can be accepted in the present form 

Back to TopTop