Deep learning in hepatocellular carcinoma:Current status and future perspectives

查看全文 作　　者：Joseph C [1]Ahn;Touseef Ahmad [2]Qureshi;Amit G [3]Singal;Debiao [2]Li;Ju-Dong [4]Yang

机构地区：[1]Gastroenterology and Hepatology,Mayo Clinic,Rochester,MN 55904,United States;[2]Biomedical Imaging Research Institute,Cedars-Sinai Medical Center,Los Angeles,CA 90048,United States;[3]Internal Medicine,University of Texas Southwestern Medical Center,Dallas,TX 75390,United States;[4]Karsh Division of Gastroenterology and Hepatology,Cedars-Sinai Medical Center,Los Angeles,CA 90048,United States

出　　处：《World Journal of Hepatology》索引2021年第13卷第12期,共13页

摘　　要：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. 关键词：Hepatocellular carcinoma Artificial intelligence Deep learning

相关文献

参考文献（65）
引证文献（4）
耦合文献（25）

参考文献(65)

引证文献(4)

耦合文献(25)

互联网出版许可证新出网证(渝)字10号全国400电话 - 免长途话费

Deep learning in hepatocellular carcinoma:Current status and future perspectives

参考文献(65)

引证文献(4)

耦合文献(25)

用户提示