Application of biological big data and radiomics in hepatocellular carcinoma

Abstract

Hepatocellular carcinoma (HCC), one of the most common gastrointestinal cancers, has been considered a worldwide threat due to its high incidence and poor prognosis. In recent years, with the continuous emergence and promotion of new sequencing technologies in omics, genomics, transcriptomics, proteomics, and liquid biopsy are used to assess HCC heterogeneity from different perspectives and become a hotspot in the field of tumor precision medicine. In addition, with the continuous improvement of machine learning algorithms and deep learning algorithms, radiomics has made great progress in the field of ultrasound, CT and MRI for HCC. This article mainly reviews the research progress of biological big data and radiomics in HCC, and it provides new methods and ideas for the diagnosis, prognosis, and therapy of HCC.