Title: A radiomics model fusing clinical features to predict microsatellite status preoperatively
in colorectal cancer liver metastasis
Version: 6 Date: 18 Jun 2023
Reviewer:  Fabio Melandro
Reviewer's report:
I read with interest the paper of Whang et al. on the role of  radiomics model to predict
microsatellite status before surgery in CRLM.
The paper is interesting, the model is well built, and the recent literature is covered.
Omics is a new argument in the field of CRLM and the authors added intriguing data tu to the
existing literature.
I completely agree with reviewer 1 and 2 about the criticism and suggestions, in particular the
introduction is too long compared to subsequent paragraphs.
In my opinion the paper could be valued for the pubblication after the revision of the reviewer
1 and 2' queries.
Title: A radiomics model fusing clinical features to predict microsatellite status preoperatively
in colorectal cancer liver metastasis
Version: 6 Date: 18 Jun 2023
Reviewer:  Fabio Melandro
Reviewer's report:
I read with interest the paper of Whang et al. on the role of  radiomics model to predict
microsatellite status before surgery in CRLM.
The paper is interesting, the model is well built, and the recent literature is covered.
Omics is a new argument in the field of CRLM and the authors added intriguing data tu to the
existing literature.
I completely agree with reviewer 1 and 2 about the criticism and suggestions, in particular the
introduction is too long compared to subsequent paragraphs.
In my opinion the paper could be valued for the pubblication after the revision of the reviewer
1 and 2' queries.
Please review this paper.
user
Title: A radiomics model fusing clinical features to predict microsatellite status preoperatively
in colorectal cancer liver metastasis
Version: 6 Date: 18 Jun 2023
Reviewer:  Fabio Melandro
Reviewer's report:
I read with interest the paper of Whang et al. on the role of  radiomics model to predict
microsatellite status before surgery in CRLM.
The paper is interesting, the model is well built, and the recent literature is covered.
Omics is a new argument in the field of CRLM and the authors added intriguing data tu to the
existing literature.
I completely agree with reviewer 1 and 2 about the criticism and suggestions, in particular the
introduction is too long compared to subsequent paragraphs.
In my opinion the paper could be valued for the pubblication after the revision of the reviewer
1 and 2' queries.
assistant