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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B
Hwi Young Kim, Pietro Lampertico, Joon Yeul Nam, et al.
Journal of Hepatology (2021) Vol. 76, Iss. 2, pp. 311-318
Closed Access | Times Cited: 89

Showing 1-25 of 89 citing articles:

Hepatocellular carcinoma
Arndt Vogel, Tim Meyer, Gonzalo Sapisochín, et al.
The Lancet (2022) Vol. 400, Iss. 10360, pp. 1345-1362
Closed Access | Times Cited: 1290
KASL clinical practice guidelines for management of chronic hepatitis B

Clinical and Molecular Hepatology (2022) Vol. 28, Iss. 2, pp. 276-331
Open Access | Times Cited: 81
Development and Validation of a Novel Model to Discriminate Idiosyncratic Drug‐Induced Liver Injury and Autoimmune Hepatitis
Yu Wang, Xuhui Lin, Ying Sun, et al.
Liver International (2025) Vol. 45, Iss. 2
Open Access | Times Cited: 1
Risk stratification and early detection biomarkers for precision HCC screening
Yi‐Te Lee, Naoto Fujiwara, Ju Dong Yang, et al.
Hepatology (2022), pp. n/a-n/a
Open Access | Times Cited: 53
An Interpretable Machine Learning Approach for Hepatitis B Diagnosis
George Obaido, Blessing Ogbuokiri, Theo G. Swart, et al.
Applied Sciences (2022) Vol. 12, Iss. 21, pp. 11127-11127
Open Access | Times Cited: 48
Artificial intelligence-assisted selection and efficacy prediction of antineoplastic strategies for precision cancer therapy
Zhe Zhang, Xiawei Wei
Seminars in Cancer Biology (2023) Vol. 90, pp. 57-72
Closed Access | Times Cited: 24
Current Status and Analysis of Machine Learning in Hepatocellular Carcinoma
Sijia Feng, Jianhua Wang, Liheng Wang, et al.
Journal of Clinical and Translational Hepatology (2023) Vol. 000, Iss. 000, pp. 000-000
Open Access | Times Cited: 22
Clinical Applications of Artificial Intelligence (AI) in Human Cancer: Is It Time to Update the Diagnostic and Predictive Models in Managing Hepatocellular Carcinoma (HCC)?
Mario Romeo, Marcello Dallio, Carmine Napolitano, et al.
Diagnostics (2025) Vol. 15, Iss. 3, pp. 252-252
Open Access | Times Cited: 1
What to do about hepatocellular carcinoma: Recommendations for health authorities from the International Liver Cancer Association
Manon Allaire, Jordi Bruix, Marko Korenjak, et al.
JHEP Reports (2022) Vol. 4, Iss. 12, pp. 100578-100578
Open Access | Times Cited: 34
Opportunities to address gaps in early detection and improve outcomes of liver cancer
Brian J. McMahon, Chari Cohen, Robert S. Brown, et al.
JNCI Cancer Spectrum (2023) Vol. 7, Iss. 3
Open Access | Times Cited: 21
Gut microbiota-based machine-learning signature for the diagnosis of alcohol-associated and metabolic dysfunction-associated steatotic liver disease
In-gyu Park, Sang Jun Yoon, Sung‐Min Won, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 6
A Liver Stiffness–Based Etiology-Independent Machine Learning Algorithm to Predict Hepatocellular Carcinoma
Huapeng Lin, Guanlin Li, Adèle Delamarre, et al.
Clinical Gastroenterology and Hepatology (2023) Vol. 22, Iss. 3, pp. 602-610.e7
Closed Access | Times Cited: 14
Diagnosis of Liver Fibrosis Using Artificial Intelligence: A Systematic Review
Stefan‐Lucian Popa, Abdulrahman Ismaiel, Ludovico Abenavoli, et al.
Medicina (2023) Vol. 59, Iss. 5, pp. 992-992
Open Access | Times Cited: 13
A machine learning model to predict liver-related outcomes after the functional cure of chronic hepatitis B
Moon Haeng Hur, Terry Cheuk‐Fung Yip, Seung Up Kim, et al.
Journal of Hepatology (2024)
Closed Access | Times Cited: 4
Single‐Cell Transcriptomic Reveals the Involvement of Cell–Cell Junctions in the Early Development of Hypertrophic Cardiomyopathy
Dingchen Wang, Lin Miao, Ruobing Wang, et al.
Journal of Cellular and Molecular Medicine (2025) Vol. 29, Iss. 3
Open Access
Effect of potent nucleos(t)ide analog on alpha fetoprotein changes and occurrence of hepatocellular carcinoma in patients with chronic hepatitis B
Qianqian Ma, Junzhao Ye, Ling Luo, et al.
Infectious Agents and Cancer (2025) Vol. 20, Iss. 1
Open Access
Evaluating the predictive value of clinical models for HBV-related hepatocellular carcinoma: A meta-analysis
Long Huang, Lu-Huai Feng, Lu Yang, et al.
Frontiers in Medicine (2025) Vol. 12
Open Access
The Malignant Transformation of Viral Hepatitis to Hepatocellular Carcinoma: Mechanisms and Interventions
Huimin Yuan, Ruochen Xu, Senlin Li, et al.
MedComm (2025) Vol. 6, Iss. 3
Open Access
Development and validation of an interpretable machine learning model for predicting the risk of hepatocellular carcinoma in patients with chronic hepatitis B: a case-control study
Linghong Wu, Jennifer Liu, Hongyuan Huang, et al.
BMC Gastroenterology (2025) Vol. 25, Iss. 1
Open Access
Machine learning-based risk assessment for cardiovascular diseases in patients with chronic lung diseases
Hongqing Xi, Q. Kang, Xunsheng Jiang
Medicine (2025) Vol. 104, Iss. 10, pp. e41672-e41672
Open Access
Is AI‐Based Hepatocellular Carcinoma Prediction Ready for Prime Time?
Xinrui Jin, Vincent Wai‐Sun Wong, Terry Cheuk‐Fung Yip
Liver International (2025) Vol. 45, Iss. 4
Closed Access
Global trends in artificial intelligence applications in liver disease over seventeen years
Xueqin Zhou, Shu Huang, Xin Shi, et al.
World Journal of Hepatology (2025) Vol. 17, Iss. 3
Closed Access
The best predictive model for hepatocellular carcinoma in patients with chronic hepatitis B infection
Jung Hwan Yu, Soon Gu Cho, Young‐Joo Jin, et al.
Clinical and Molecular Hepatology (2021) Vol. 28, Iss. 3, pp. 351-361
Open Access | Times Cited: 28
iPADD: A Computational Tool for Predicting Potential Antidiabetic Drugs Using Machine Learning Algorithms
Xiaowei Liu, Tianyu Shi, Dong Gao, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 15, pp. 4960-4969
Closed Access | Times Cited: 11
Comparable outcomes between immune-tolerant and active phases in noncirrhotic chronic hepatitis B: a meta-analysis
Han Ah Lee, Seung Up Kim, Yeon Seok Seo, et al.
Hepatology Communications (2023) Vol. 7, Iss. 2, pp. e0011-e0011
Open Access | Times Cited: 10
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