Predicting Objective Response Rate (ORR) in Immune Checkpoint Inhibitor (ICI) Therapies with Machine Learning (ML) by Combining Clinical and Patient-Reported Data
and Jussi P. Koivunen 1
Round 1
Reviewer 1 Report
The article "Predicting objective response rate (ORR) in immune checkpoint inhibitor (ICI) therapies with machine learning (ML) by combining clinical and patient-reported data" proposes an ML model to predict the overall response rate (ORR) in cancer patients. This paper is a well-written article with a straightforward approach and clear message.
There are some general and specific comments for the betterment of the manuscript.
1- It is undeniable that AI is taking over everything and can be utilised in biomedical research when predicting a treatment outcome. As the biomedical scientists and health professionals are the potential readers of this paper, I recommend adding a table including demographical data of the patients (sex, age, literacy status, type of cancer, stage, etc.) to make the paper look more clinical.
2- the images are poorly presented. If this is the writer's responsibility, please make sure to upload high-quality images/tables and perhaps provide searchable formats.
3- The manuscript is replete with typographical and grammatical errors. It is highly suggested that native speakers do another round of proofreading. The abstract starts with a common language mistake: "ICIs are a standard of care..." which must be corrected to either " ICIs are standards of care...", or "ICI is a standard of care..." Please also refer to the attached PDF with some more comments for the discussion/conclusion part.
Stay safe...
Comments for author File: 
Comments.pdf
Author Response
1) We have added a Table of demographics
2) The figures have no been edited for higher resolution
3) English-proof reading has taken place and manuscript has been edited based on that.
Reviewer 2 Report
Dear Authors,
Please extent, improve your introduction with more references.
Please extent, improve your discussion with more references.
Please add more conclusions to your research
Kind regards
Author Response
1) We have added text and references to the Introduction.
2) We have also added text and references to the Discussion.
3) The Conclusion chapter has been extended.
