Title: Establishing machine learning models to predict the early risk of gastric cancer based on
lifestyle factors
Version: 1 Date: 05 Aug 2022
Reviewer:  Deepak Painuli
Reviewer's report:
Article seems to be good paper related to Establishing Machine Learning models to predict
early risk of Gastric cancer. However, submitted manuscript needs some minor revision (stated
below).
* Comparison with old studies needs to be introduced in section – 1 rather than discussion
section.
* Introduction to machine learning may be incorporated in introduction section for novice non-
technical reader of researchers.
* Reason for selecting specific six ML models (utilised in this paper) may be needed to add
on clear cut separation line among used models and rest of ML models, which are not utilised
during this study.
* Paper structure/organisation need to be defined at last paragraph of introduction section for
ease of navigation throughout paper.
* Proper alignment of Figure -1 is required as manuscript text is hidden by image.
* It seems dataset is imbalanced (leading to biased prediction by model), no data imbalance
method is used or described in manuscript text or if used than not disclosed in manuscript.
* Accuracy metrics is fruitful only in balanced dataset. However, dataset seems to be
imbalanced.
* Please mention table no in page no-11 while discussing about performance of KNN.
* Accuracy of stated best classifier (XGBoost) is fair enough, however it may be improved
kindly state in future scope.
* Some more recent studies related to cancer diagnosis using machine learning may be
incorporated in reference.
Title: Establishing machine learning models to predict the early risk of gastric cancer based on
lifestyle factors
Version: 1 Date: 05 Aug 2022
Reviewer:  Deepak Painuli
Reviewer's report:
Article seems to be good paper related to Establishing Machine Learning models to predict
early risk of Gastric cancer. However, submitted manuscript needs some minor revision (stated
below).
* Comparison with old studies needs to be introduced in section – 1 rather than discussion
section.
* Introduction to machine learning may be incorporated in introduction section for novice non-
technical reader of researchers.
* Reason for selecting specific six ML models (utilised in this paper) may be needed to add
on clear cut separation line among used models and rest of ML models, which are not utilised
during this study.
* Paper structure/organisation need to be defined at last paragraph of introduction section for
ease of navigation throughout paper.
* Proper alignment of Figure -1 is required as manuscript text is hidden by image.
* It seems dataset is imbalanced (leading to biased prediction by model), no data imbalance
method is used or described in manuscript text or if used than not disclosed in manuscript.
* Accuracy metrics is fruitful only in balanced dataset. However, dataset seems to be
imbalanced.
* Please mention table no in page no-11 while discussing about performance of KNN.
* Accuracy of stated best classifier (XGBoost) is fair enough, however it may be improved
kindly state in future scope.
* Some more recent studies related to cancer diagnosis using machine learning may be
incorporated in reference.
Please review this paper.
user
Title: Establishing machine learning models to predict the early risk of gastric cancer based on
lifestyle factors
Version: 1 Date: 05 Aug 2022
Reviewer:  Deepak Painuli
Reviewer's report:
Article seems to be good paper related to Establishing Machine Learning models to predict
early risk of Gastric cancer. However, submitted manuscript needs some minor revision (stated
below).
* Comparison with old studies needs to be introduced in section – 1 rather than discussion
section.
* Introduction to machine learning may be incorporated in introduction section for novice non-
technical reader of researchers.
* Reason for selecting specific six ML models (utilised in this paper) may be needed to add
on clear cut separation line among used models and rest of ML models, which are not utilised
during this study.
* Paper structure/organisation need to be defined at last paragraph of introduction section for
ease of navigation throughout paper.
* Proper alignment of Figure -1 is required as manuscript text is hidden by image.
* It seems dataset is imbalanced (leading to biased prediction by model), no data imbalance
method is used or described in manuscript text or if used than not disclosed in manuscript.
* Accuracy metrics is fruitful only in balanced dataset. However, dataset seems to be
imbalanced.
* Please mention table no in page no-11 while discussing about performance of KNN.
* Accuracy of stated best classifier (XGBoost) is fair enough, however it may be improved
kindly state in future scope.
* Some more recent studies related to cancer diagnosis using machine learning may be
incorporated in reference.
assistant