Artificial Intelligence, Machine Learning, and Deep Learning in the Diagnosis and Management of Hepatocellular Carcinoma

Round 1

Reviewer 1 Report

·       This manuscript provides a comprehensive review of the potential applications of Artificial Intelligence (AI), Machine Learning, and Deep Learning in the diagnosis and management of hepatocellular carcinoma (HCC). The authors effectively highlight the expanding role of AI in medicine and its potential to assist clinicians in making complex treatment decisions.

·       The inclusion of preliminary studies demonstrating the superiority of AI algorithms in predicting the development of HCC compared to standard models is particularly noteworthy. The manuscript also discusses the application of radiomics and deep learning methodologies, showcasing their potential in aiding diagnosis, prognostication, and risk stratification in HCC patients.

·       The authors appropriately acknowledge the need for further clinical validation and generalizability through larger and more diverse populations. This recognition of the current limitations of AI in HCC management strengthens the manuscript's credibility and underscores the importance of ongoing research in this rapidly evolving field.

·       Overall, this manuscript effectively presents the promising applications of AI in the diagnosis and management of HCC, providing valuable insights for clinicians and researchers working in this domain.

Author Response

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Reviewer 2 Report

the research framework is very interesting and the use of AI in clinical practice is fast developing in modern science and medicine. the authors made effort and summarized recent findings about that subject. the introduction are very informative with enough information about similar research. the composition of the review article is very good and easy to follow the main idea. the authors analyze all advantages and disadvantages of the use AI in the clinical practice and pointed out use of the machine learning in the improvement of clinical practice in determining diagnosis and potential medicinal treatments. 

in the conclusion the authors pointed out that this is still developing techniques with bright future.

the English style and grammar are fine easy to read and to follow the main framework of the presented studies.

Author Response

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Reviewer 3 Report

In this review, the author examines the potential of artificial intelligence in treating hepatocellular carcinoma (HCC). I personally believe that this review requires substantial improvement. For instance:

(1) To enhance the comprehensibility of "Screening and Detection", the author should include pertinent summary graphs or tables in certain sections.

(2) In the section titled "HCC Prognosis and Risk of Recurrence", the authors should compare and summarize the prognostic risk factors from existing studies, explain the research methods used, and describe any differences between methods, preferably in a tabular format.

(3) In the "Pathologic Assessment", the author should provide the data style and explain the research methods used, along with the differences and similarities between the methods, and it would be best to use a tabular format.

(4) Similarly, in the articles "Locoregional Therapies", "Automatic Methods for Liver and Tumor Segmentation", and "Surgical Complications", the authors should also explain the research methods used and any differences between methods, preferably in a tabular format.

Author Response

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Reviewer 4 Report

Nice review.

Can you please add how AI can tackle racial, ethnic and socioeconomic diversity in different countries.

Can you please add relevance of AI in running the tumor boards.

Can you please add few lines on AI and insurance reimbursement.

Can you please add a paragraph on how to store and protect the large data set while sharing with different institutes from different countries.

Authors think the health care cost will go up or down if we start using AI. Please add few lines on this.

Author Response

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Round 2

Reviewer 3 Report

The revised version by the author is much stronger in quality compared to the previous version, and I don't have any other suggestions on my end.