Research on multi-model imaging machine learning for distinguishing early hepatocellular carcinoma.

ABSTRACT:

Objective

To investigate the value of differential diagnosis of hepatocellular carcinoma (HCC) and non-hepatocellular carcinoma (non-HCC) based on CT and MR multiphase radiomics combined with different machine learning models and compare the diagnostic efficacy between different radiomics models.

Background

Primary liver cancer is one of the most common clinical malignancies, hepatocellular carcinoma (HCC) is the most common subtype of primary liver cancer, accounting for approximately 90% of cases. A clear diagnosis of HCC is important for the individualized treatment of patients with HCC. However, more sophisticated diagnostic modalities need to be explored.

Methods

This retrospective study included 211 patients with liver lesions: 97 HCC and 124 non-hepatocellular

SUBMITTER: Ma Y 

PROVIDER: S-EPMC10956394 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature