Title: Machine Learning-Based Survival Rate Prediction of Korean Hepatocellular Carcinoma
Patients using multi-center data
Version: 6 Date: 27 Dec 2021
Reviewer's report:
Researchers use a variety of machine learning algorithms to predict the survival rate of patients
with hepatocellular carcinoma, which has certain significance for assessing the accuracy of the
machine learning method, but the clinical value is not very significant enough. In addition, there
are some obscurers in writing, some methodological parts of the paper are not clear enough.
Moreover, there are many obvious problems such as inappropriate punctuations and repetitive
text. The content and language of the article that require deep polishing. What’s more, the
figures and tables typography are also not standard enough. Particularly, in Fig.3 and Fig.4 I
cannot understand the processing method corresponding to each picture. The characteristics of
the patients are not consistent but disordered. I believe it is not very difficult to arrange the
features in each picture in the same order. In addition, the authors shall provide more detailes of
the methods and decribe them with logical approach. In short, the article needs to make extensive
revisions.
Title: Machine Learning-Based Survival Rate Prediction of Korean Hepatocellular Carcinoma
Patients using multi-center data
Version: 6 Date: 27 Dec 2021
Reviewer's report:
Researchers use a variety of machine learning algorithms to predict the survival rate of patients
with hepatocellular carcinoma, which has certain significance for assessing the accuracy of the
machine learning method, but the clinical value is not very significant enough. In addition, there
are some obscurers in writing, some methodological parts of the paper are not clear enough.
Moreover, there are many obvious problems such as inappropriate punctuations and repetitive
text. The content and language of the article that require deep polishing. What’s more, the
figures and tables typography are also not standard enough. Particularly, in Fig.3 and Fig.4 I
cannot understand the processing method corresponding to each picture. The characteristics of
the patients are not consistent but disordered. I believe it is not very difficult to arrange the
features in each picture in the same order. In addition, the authors shall provide more detailes of
the methods and decribe them with logical approach. In short, the article needs to make extensive
revisions.
Please review this paper.
user
Title: Machine Learning-Based Survival Rate Prediction of Korean Hepatocellular Carcinoma
Patients using multi-center data
Version: 6 Date: 27 Dec 2021
Reviewer's report:
Researchers use a variety of machine learning algorithms to predict the survival rate of patients
with hepatocellular carcinoma, which has certain significance for assessing the accuracy of the
machine learning method, but the clinical value is not very significant enough. In addition, there
are some obscurers in writing, some methodological parts of the paper are not clear enough.
Moreover, there are many obvious problems such as inappropriate punctuations and repetitive
text. The content and language of the article that require deep polishing. What’s more, the
figures and tables typography are also not standard enough. Particularly, in Fig.3 and Fig.4 I
cannot understand the processing method corresponding to each picture. The characteristics of
the patients are not consistent but disordered. I believe it is not very difficult to arrange the
features in each picture in the same order. In addition, the authors shall provide more detailes of
the methods and decribe them with logical approach. In short, the article needs to make extensive
revisions.
assistant