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Nov 14, 2020 (publication date) through Jul 18, 2025
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World Journal of Gastroenterology
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1007-9327
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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
| For: | Lai Q, Spoletini G, Mennini G, Larghi Laureiro Z, Tsilimigras DI, Pawlik TM, Rossi M. Prognostic role of artificial intelligence among patients with hepatocellular cancer: A systematic review. World J Gastroenterol 2020; 26(42): 6679-6688 [PMID: 33268955 DOI: 10.3748/wjg.v26.i42.6679] |
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| URL: | https://www.wjgnet.com/1948-5204/full/v26/i42/6679.htm |
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| 1 |
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Chunxiao Sui, Qian Su, Kun Chen, Rui Tan, Ziyang Wang, Zifan Liu, Wengui Xu, Xiaofeng Li. 18F-FDG PET/CT-based habitat radiomics combining stacking ensemble learning for predicting prognosis in hepatocellular carcinoma: a multi-center study. BMC Cancer 2024; 24(1) doi: 10.1186/s12885-024-13206-5
|
| 3 |
Haopeng Kuang, Zhongwei Yang, Xukun Zhang, Shunli Wang, Lihua Zhang. A Review of Artificial Intelligence in Preoperative Clinical Staging of Liver Cancer. 2021 International Conference on Networking Systems of AI (INSAI) 2021; : 69 doi: 10.1109/INSAI54028.2021.00024
|
| 4 |
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|
| 5 |
Xiaoyang Liu, Mohamed G. Elbanan, Antonio Luna, Masoom A. Haider, Andrew D. Smith, Carl F. Sabottke, Bradley M. Spieler, Baris Turkbey, David Fuentes, Ahmed Moawad, Serageldin Kamel, Natally Horvat, Khaled M. Elsayes. Radiomics in Abdominopelvic Solid-Organ Oncologic Imaging: Current Status. American Journal of Roentgenology 2022; 219(6): 985 doi: 10.2214/AJR.22.27695
|
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Sheza Malik, Rishi Das, Thanita Thongtan, Kathryn Thompson, Nader Dbouk. AI in Hepatology: Revolutionizing the Diagnosis and Management of Liver Disease. Journal of Clinical Medicine 2024; 13(24): 7833 doi: 10.3390/jcm13247833
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Sachin C Sarode, Nilesh Kumar Sharma, Gargi Sarode. A Critical Appraisal on Cancer Prognosis and Artificial Intelligence. Future Oncology 2022; 18(13): 1531 doi: 10.2217/fon-2021-1528
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|
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|
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|
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|
| 31 |
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|
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|
| 33 |
Zhenxing Jiang, Lizhao Yan, Shenghe Deng, Junnan Gu, Le Qin, Fuwei Mao, Yifan Xue, Wentai Cai, Xiu Nie, Hongli Liu, Fumei Shang, Kaixiong Tao, Jiliang Wang, Ke Wu, Yinghao Cao, Kailin Cai, Xing Niu. Development and Interpretation of a Clinicopathological-Based Model for the Identification of Microsatellite Instability in Colorectal Cancer. Disease Markers 2023; 2023: 1 doi: 10.1155/2023/5178750
|
| 34 |
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|
| 35 |
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|
| 36 |
Vincenza Granata, Roberta Grassi, Roberta Fusco, Andrea Belli, Carmen Cutolo, Silvia Pradella, Giulia Grazzini, Michelearcangelo La Porta, Maria Chiara Brunese, Federica De Muzio, Alessandro Ottaiano, Antonio Avallone, Francesco Izzo, Antonella Petrillo. Diagnostic evaluation and ablation treatments assessment in hepatocellular carcinoma. Infectious Agents and Cancer 2021; 16(1) doi: 10.1186/s13027-021-00393-0
|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
Vinícius Remus Ballotin, Lucas Goldmann Bigarella, John Soldera, Jonathan Soldera. Deep learning applied to the imaging diagnosis of hepatocellular carcinoma. Artificial Intelligence in Gastrointestinal Endoscopy 2021; 2(4): 127-135 doi: 10.37126/aige.v2.i4.127
|
| 42 |
Zoe Y. Lu, Mohammad Q. Maki, Madhukar S. Patel, Tommy Ivanics. Transplant Oncology. 2025; : 191 doi: 10.1016/B978-0-443-21901-6.00016-1
|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
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|
| 48 |
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|
| 49 |
Riccardo DE ROBERTIS, Flavio SPOTO, Francesca PASQUAZZO, Mirko D’ONOFRIO. Clinical applications of radiomics and artificial intelligence: prognostic stratification and response to treatment. Journal of Radiological Review 2023; 10(3) doi: 10.23736/S2723-9284.23.00245-9
|
| 50 |
Yun Qin, Li-Hua Zhu, Wei Zhao, Jun-Jie Wang, Hao Wang. Review of Radiomics- and Dosiomics-based Predicting Models for Rectal Cancer. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.913683
|
| 51 |
Francesca Romana Ponziani, Edoardo G. Giannini, Quirino Lai. Machine learning and biomarkers in hepatocellular carcinoma: The future is now. Liver Cancer International 2022; 3(3): 111 doi: 10.1002/lci2.67
|
| 52 |
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|