Research Progress in Artificial Intelligence for Diagnosis， Prediction of Recurrence and Prognosis in Hepatocellular Carcinoma

CHENG Zhao-rui; WANG Tong

doi:10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2023.0602

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Research Progress in Artificial Intelligence for Diagnosis， Prediction of Recurrence and Prognosis in Hepatocellular Carcinoma

Review | 更新时间：2024-02-19

- Research Progress in Artificial Intelligence for Diagnosis， Prediction of Recurrence and Prognosis in Hepatocellular Carcinoma
- Journal of Sun Yat-sen University(Medical Sciences) Vol. 44, Issue 6, Pages: 903-909(2023)
- 作者机构：
  
  中山大学附属第八医院急诊科，广东深圳，518033
- 作者简介：
  
  WANG Tong； E-mail： tongwang316@163.com
- 基金信息：
- DOI：10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2023.0602
  CLC： R735.7
- Published：20 November 2023，
  
  Received：01 May 2023，
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程兆瑞,王彤.人工智能技术在肝细胞癌诊断、复发及预后预测研究进展[J].中山大学学报（医学科学版）,2023,44(06):903-909.

CHENG Zhao-rui,WANG Tong.Research Progress in Artificial Intelligence for Diagnosis， Prediction of Recurrence and Prognosis in Hepatocellular Carcinoma[J].Journal of Sun Yat-sen University(Medical Sciences),2023,44(06):903-909.
程兆瑞,王彤.人工智能技术在肝细胞癌诊断、复发及预后预测研究进展[J].中山大学学报（医学科学版）,2023,44(06):903-909. DOI： 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2023.0602.

CHENG Zhao-rui,WANG Tong.Research Progress in Artificial Intelligence for Diagnosis， Prediction of Recurrence and Prognosis in Hepatocellular Carcinoma[J].Journal of Sun Yat-sen University(Medical Sciences),2023,44(06):903-909. DOI： 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2023.0602.

摘要

随着人工智能（AI）技术在医学领域的迅速发展，AI模型在肝细胞癌（HCC）诊断、预测预后和疗效方面展现了巨大的潜力。AI技术包括计算搜索算法、机器学习（ML）和深度学习（DL）模型。基于组织病理学、放射学图像及相关分子标志物，利用ML或DL算法提取关键信息，建立的诊断或预测模型有望作为决策辅助工具应用于临床。然而，AI模型的应用尚存在局限性，需要进一步的技术支持、大规模临床验证和监管批准。本文总结了人工智能技术在肝细胞癌诊断、复发及预后预测方面研究进展，特别关注放射组学、组织病理学及分子标志物相关数据。

Abstract

With the rapid development of artificial intelligence （AI） technology in the field of medicine， AI models show great potential in the diagnosis， prognosis and efficacy prediction of hepatocellular carcinoma （HCC）. AI techniques include computational search algorithms， machine learning （ML） and deep learning （DL） models. Based on histopathology， radiomics and related molecular markers， the ML or DL algorithm is used to extract key information and then establish the diagnosis or prediction model， which may serve as a tool to aid in clinical decision-making. Further technical support， large-scale clinical validation and regulatory approvals are still needed due to the limitations on the application of AI models. This review summarizes the advances of AI in HC diagnosis， prediction of recurrence and prognosis， and highlights the radiomics， histopathology and molecular marker data.

关键词

人工智能技术肝细胞癌影像组学组织病理学诊断预测

Keywords

artificial intelligencetechnologyhepatocellular carcinomaradiomicshistopathologydiagnosisprediction

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