Deep learning in hepatocellular carcinoma: Current status and future perspectives

Joseph C. Ahn, Touseef Ahmad Qureshi, Debiao Li, Amit G. Singal, Ju Dong Yang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Hepatocellular carcinoma (HCC) is among the leading causes of cancer incidence and death. Despite decades of research and development of new treatment options, the overall outcomes of patients with HCC continue to remain poor. There are areas of unmet need in risk prediction, early diagnosis, accurate prognostication, and individualized treatments for patients with HCC. Recent years have seen an explosive growth in the application of artificial intelligence (AI) technology in medical research, with the field of HCC being no exception. Among the various AI-based machine learning algorithms, deep learning algorithms are considered state-of-the-art techniques for handling and processing complex multimodal data ranging from routine clinical variables to high-resolution medical images. This article will provide a comprehensive review of the recently published studies that have applied deep learning for risk prediction, diagnosis, prognostication, and treatment planning for patients with HCC.

Original languageEnglish (US)
Pages (from-to)2039-2051
Number of pages13
JournalWorld Journal of Hepatology
Volume13
Issue number12
DOIs
StatePublished - 2021

Keywords

  • Artificial intelligence
  • Deep learning
  • Hepatocellular carcinoma

ASJC Scopus subject areas

  • Hepatology

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