Discussion
dissimilar hepatic diseases, liver malignancies, metabolic diseases, HCC, tumors
RECURRENCE, INFILTRATION, VIRAL HEPATITIS, METABOLIC DISEASES, TUMORS, DISEASES
With the rapid advances in radiology, more and more liver malignancies are being detected early and operated in a timely manner, which greatly improves patient survival. However, the recurrence rate of HCC remains high, and the 5-year survival rate of HCC patients is just 15% [At present, the factors that predict MVI include the size and number of tumors, serum AFP, and the degree of lymphocyte infiltration in the liver tissue [Recently, artificial intelligence technology represented by machine learning has witnessed rapid progress and has been extensively applied in auxiliary diagnosis, prognostic analysis, and personalized diagnosis and treatment of diseases [This study had several limitations. First, the limited number of samples leaves the question open on the statistical power; therefore, we should continue to collect more samples. Second, this is a small-sample exploratory study in a single center. it is necessary to validate the results from other centers. A multicenter study with a larger population would contribute to verifying the present results of OSS in the future. Third, considering the sample was mostly composed by patients stricken by viral hepatitis, with few cases of metabolic diseases in this study. Therefore, using this model to predict MVI caused by dissimilar hepatic diseases may require further verification.This study is the first to explore the nomogram prediction model based on differential protein expression in HCC tissues. This model has high reliability and clinical application potential and could therefore be used as an important method in the diagnosis and prediction of MVI.