Title: Establishing machine learning models to predict the early risk of gastric cancer based on
lifestyle factors
Version: 1 Date: 14 Aug 2022
Reviewer's report:
This study aimed to develop a machine learning model to predict gastric cancer using life style
factors. I think the results of this study is useful in real-world clinical practice, and the risk factors
selected by the "Relief Feature Selection Algorithm" is compatible to previous knowledges of
gastric cancer. I only have a comment regarding the possibility of developing a explainable
machine model using SHAP methods in your dataset. SHAP method can explain the machine
learning model at cohort level and at the individual patient level . Further analysis using SHAP
method to interpret your model may increase  their utility in clinical practice.
Title: Establishing machine learning models to predict the early risk of gastric cancer based on
lifestyle factors
Version: 1 Date: 14 Aug 2022
Reviewer's report:
This study aimed to develop a machine learning model to predict gastric cancer using life style
factors. I think the results of this study is useful in real-world clinical practice, and the risk factors
selected by the "Relief Feature Selection Algorithm" is compatible to previous knowledges of
gastric cancer. I only have a comment regarding the possibility of developing a explainable
machine model using SHAP methods in your dataset. SHAP method can explain the machine
learning model at cohort level and at the individual patient level . Further analysis using SHAP
method to interpret your model may increase  their utility in clinical practice.
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: 14 Aug 2022
Reviewer's report:
This study aimed to develop a machine learning model to predict gastric cancer using life style
factors. I think the results of this study is useful in real-world clinical practice, and the risk factors
selected by the "Relief Feature Selection Algorithm" is compatible to previous knowledges of
gastric cancer. I only have a comment regarding the possibility of developing a explainable
machine model using SHAP methods in your dataset. SHAP method can explain the machine
learning model at cohort level and at the individual patient level . Further analysis using SHAP
method to interpret your model may increase  their utility in clinical practice.
assistant