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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:

Deep Learning for Accurate Diagnosis of Liver Tumor Based on Magnetic Resonance Imaging and Clinical Data
Shihui Zhen, Ming Cheng, Yu-bo Tao, et al.
Frontiers in Oncology (2020) Vol. 10
Open Access | Times Cited: 167

Showing 1-25 of 167 citing articles:

Artificial intelligence and machine learning for medical imaging: A technology review
Ana María Barragán Montero, Umair Javaid, Gilmer Valdés, et al.
Physica Medica (2021) Vol. 83, pp. 242-256
Open Access | Times Cited: 270
Artificial intelligence for the prevention and clinical management of hepatocellular carcinoma
Julien Caldéraro, Tobias Paul Seraphin, Tom Luedde, et al.
Journal of Hepatology (2022) Vol. 76, Iss. 6, pp. 1348-1361
Open Access | Times Cited: 194
Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction
David Nam, Julius Chapiro, Valérie Paradis, et al.
JHEP Reports (2022) Vol. 4, Iss. 4, pp. 100443-100443
Open Access | Times Cited: 140
A Review of Explainable Deep Learning Cancer Detection Models in Medical Imaging
Mehmet A. Gulum, Christopher M. Trombley, Mehmed Kantardzic
Applied Sciences (2021) Vol. 11, Iss. 10, pp. 4573-4573
Open Access | Times Cited: 105
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: 2
Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis
Liyun Xue, Zhuoyun Jiang, Tiantian Fu, et al.
European Radiology (2020) Vol. 30, Iss. 5, pp. 2973-2983
Open Access | Times Cited: 96
Advances in Deep Learning-Based Medical Image Analysis
Xiaoqing Liu, Kunlun Gao, Bo Liu, et al.
Health Data Science (2021) Vol. 2021
Open Access | Times Cited: 88
Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency
Ana María Barragán Montero, Adrien Bibal, Margerie Huet Dastarac, et al.
Physics in Medicine and Biology (2022) Vol. 67, Iss. 11, pp. 11TR01-11TR01
Open Access | Times Cited: 51
Artificial intelligence in liver cancers: Decoding the impact of machine learning models in clinical diagnosis of primary liver cancers and liver cancer metastases
Anita K. Bakrania, Narottam Joshi, Xun Zhao, et al.
Pharmacological Research (2023) Vol. 189, pp. 106706-106706
Open Access | Times Cited: 40
Fully Automatic Liver and Tumor Segmentation from CT Image Using an AIM-Unet
Fırat Özcan, Osman Nuri Uçan, Songül Çavdar Karaçam, et al.
Bioengineering (2023) Vol. 10, Iss. 2, pp. 215-215
Open Access | Times Cited: 36
Artificial intelligence in liver cancer — new tools for research and patient management
Julien Caldéraro, Laura Žigutytė, Daniel Truhn, et al.
Nature Reviews Gastroenterology & Hepatology (2024) Vol. 21, Iss. 8, pp. 585-599
Closed Access | Times Cited: 12
The power of deep learning in simplifying feature selection for hepatocellular carcinoma: a review
G. Mostafa, Hamdi A. Mahmoud, Tarek Abd El‐Hafeez, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 10
Cancer Detection Using Artificial Intelligence: A Paradigm in Early Diagnosis
Gayathri Bulusu, K. E. Ch. Vidyasagar, Malini Mudigonda, et al.
Archives of Computational Methods in Engineering (2025)
Open Access | Times Cited: 1
Skin lesion classification in dermoscopic images using stacked Convolutional Neural Network
Ahmad Hameed, Muhammad Umer, Umair Hafeez, et al.
Journal of Ambient Intelligence and Humanized Computing (2021) Vol. 14, Iss. 4, pp. 3551-3565
Closed Access | Times Cited: 47
Artificial intelligence: A review of current applications in hepatocellular carcinoma imaging
Anna Pellat, Maxime Barat, Romain Coriat, et al.
Diagnostic and Interventional Imaging (2022) Vol. 104, Iss. 1, pp. 24-36
Open Access | Times Cited: 29
Computerized Diagnosis of Liver Tumors From CT Scans Using a Deep Neural Network Approach
Abhishek Midya, Jayasree Chakraborty, Rami Srouji, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 27, Iss. 5, pp. 2456-2464
Open Access | Times Cited: 20
The Diagnostic Approach towards Combined Hepatocellular-Cholangiocarcinoma—State of the Art and Future Perspectives
Johannes Eschrich, Zuzanna Kobus, Dominik Geisel, et al.
Cancers (2023) Vol. 15, Iss. 1, pp. 301-301
Open Access | Times Cited: 18
Artificial intelligence in hepatocellular carcinoma diagnosis: a comprehensive review of current literature
Odysseas P. Chatzipanagiotou, Constantinos Loukas, Michail Vailas, et al.
Journal of Gastroenterology and Hepatology (2024) Vol. 39, Iss. 10, pp. 1994-2005
Open Access | Times Cited: 6
Synthesis of gadolinium-enhanced liver tumors on nonenhanced liver MR images using pixel-level graph reinforcement learning
Chenchu Xu, Dong Zhang, Jaron Chong, et al.
Medical Image Analysis (2021) Vol. 69, pp. 101976-101976
Closed Access | Times Cited: 36
Deep learning in hepatocellular carcinoma: Current status and future perspectives
Joseph Ahn, Touseef Ahmad Qureshi, Amit G. Singal, et al.
World Journal of Hepatology (2021) Vol. 13, Iss. 12, pp. 2039-2051
Open Access | Times Cited: 34
Automatic Detection of Liver Cancer Using Hybrid Pre-Trained Models
Esam Othman, Muhammad Mahmoud, Habib Dhahri, et al.
Sensors (2022) Vol. 22, Iss. 14, pp. 5429-5429
Open Access | Times Cited: 24
MANet: a multi-attention network for automatic liver tumor segmentation in computed tomography (CT) imaging
Kasun Gayashan Hettihewa, Thananop Kobchaisawat, Natthaporn Tanpowpong, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 13
Segmentation of liver and liver lesions using deep learning
Maryam Fallahpoor, Dan Nguyen, Ehsan Montahaei, et al.
Physical and Engineering Sciences in Medicine (2024) Vol. 47, Iss. 2, pp. 611-619
Closed Access | Times Cited: 5
Prediction model of early recurrence of multimodal hepatocellular carcinoma with tensor fusion
Tianyi Wang, Haimei Chen, Zebin Chen, et al.
Physics in Medicine and Biology (2024) Vol. 69, Iss. 12, pp. 125003-125003
Closed Access | Times Cited: 5
Artificial Intelligence for Detecting and Quantifying Fatty Liver in Ultrasound Images: A Systematic Review
Fahad Muflih Alshagathrh, Mowafa Househ
Bioengineering (2022) Vol. 9, Iss. 12, pp. 748-748
Open Access | Times Cited: 22
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