Current Status and Analysis of Machine Learning in Hepatocellular Carcinoma-Reference-Cited by-同舟云学术

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Current Status and Analysis of Machine Learning in Hepatocellular Carcinoma

Published:2023-05-17 Issue:000 Volume:000 Page:000-000
ISSN:2225-0719
Container-title:Journal of Clinical and Translational Hepatology
language:en
Short-container-title:J Clin Transl Hepatol

Author:

Feng Sijia^ORCID,Wang Jianhua,Wang Liheng,Qiu Qixuan,Chen Dongdong,Su Huo,Li Xiaoli,Xiao Yao^ORCID,Lin Chiayen^ORCID

Publisher

Xia & He Publishing

Subject

Hepatology

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Promising Directions in Radiation Diagnostics of Oncopathology – Potentials of Radiomics in Digital Analysis of Features of Hepatocellular Carcinoma;Journal of Experimental and Clinical Surgery;2024-08-18

2. Impact of an artificial intelligence based model to predict non-transplantable recurrence among patients with hepatocellular carcinoma;HPB;2024-08

3. Multiple machine learning algorithms identified SLC6A8 as a diagnostic biomarker of the late stage of Hepatocellular carcinoma;2024-07-12

4. Breaking Down the Arsenal: Recent Progress in the Nanotherapeutic Strategies for Hepatocellular Carcinoma Treatment;Advanced Therapeutics;2024-07-06

5. Deep learning models for predicting the survival of patients with hepatocellular carcinoma based on a surveillance, epidemiology, and end results (SEER) database analysis;Scientific Reports;2024-06-09

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