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/1007-9327/full/v26/i42/6679.htm |
Number | Citing Articles |
1 |
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
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2 |
Mahmoud Y. Shams, El-Sayed M. El-kenawy, Abdelhameed Ibrahim, Ahmed M. Elshewey. A hybrid dipper throated optimization algorithm and particle swarm optimization (DTPSO) model for hepatocellular carcinoma (HCC) prediction. Biomedical Signal Processing and Control 2023; 85: 104908 doi: 10.1016/j.bspc.2023.104908
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3 |
Benoit Schmauch, Sarah S. Elsoukkary, Amika Moro, Roma Raj, Chase J. Wehrle, Kazunari Sasaki, Julien Calderaro, Patrick Sin-Chan, Federico Aucejo, Daniel E. Roberts. Combining a deep learning model with clinical data better predicts hepatocellular carcinoma behavior following surgery. Journal of Pathology Informatics 2023; : 100360 doi: 10.1016/j.jpi.2023.100360
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4 |
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
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5 |
Jan Lerut. Modern technology, liver surgery and transplantation. Hepatobiliary & Pancreatic Diseases International 2022; 21(4): 307 doi: 10.1016/j.hbpd.2022.06.006
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6 |
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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7 |
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
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8 |
Antonio Martinez-Millana, Aida Saez-Saez, Roberto Tornero-Costa, Natasha Azzopardi-Muscat, Vicente Traver, David Novillo-Ortiz. Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews. International Journal of Medical Informatics 2022; 166: 104855 doi: 10.1016/j.ijmedinf.2022.104855
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9 |
Christopher A. Lovejoy, Saleh A. Alqahtani. AI in colonoscopy and beyond: On the cusp of clinical implementation?. United European Gastroenterology Journal 2021; 9(5): 525 doi: 10.1002/ueg2.12076
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10 |
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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11 |
Vincenza Granata, Roberta Fusco, Sergio Venazio Setola, Igino Simonetti, Diletta Cozzi, Giulia Grazzini, Francesca Grassi, Andrea Belli, Vittorio Miele, Francesco Izzo, Antonella Petrillo. An update on radiomics techniques in primary liver cancers. Infectious Agents and Cancer 2022; 17(1) doi: 10.1186/s13027-022-00422-6
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12 |
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
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13 |
Aleksander Krasowski, Joachim Krois, Adelheid Kuhlmey, Hendrik Meyer-Lueckel, Falk Schwendicke. Predicting mortality in the very old: a machine learning analysis on claims data. Scientific Reports 2022; 12(1) doi: 10.1038/s41598-022-21373-3
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14 |
Amene Saghazadeh, Nima Rezaei. Handbook of Cancer and Immunology. 2023; : 1 doi: 10.1007/978-3-030-80962-1_309-1
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15 |
Gary R. Schooler, Juan C. Infante, Michael Acord, Adina Alazraki, Govind B. Chavhan, James Christopher Davis, Geetika Khanna, Ajaykumar C. Morani, Cara E. Morin, HaiThuy N. Nguyen, Mitchell A. Rees, Raja Shaikh, Abhay Srinivasan, Judy H. Squires, Elizabeth Tang, Paul G. Thacker, Alexander J. Towbin. Imaging of pediatric liver tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee White Paper. Pediatric Blood & Cancer 2023; 70(S4) doi: 10.1002/pbc.29965
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16 |
Qiuxia Wei, Nengren Tan, Shiyu Xiong, Wanrong Luo, Haiying Xia, Baoming Luo. Deep Learning Methods in Medical Image-Based Hepatocellular Carcinoma Diagnosis: A Systematic Review and Meta-Analysis. Cancers 2023; 15(23): 5701 doi: 10.3390/cancers15235701
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17 |
Afrouz Ataei, Jun Deng, Wazir Muhammad. Liver cancer risk quantification through an artificial neural network based on personal health data. Acta Oncologica 2023; 62(5): 495 doi: 10.1080/0284186X.2023.2213445
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18 |
Dalia Fahmy, Ahmed Alksas, Ahmed Elnakib, Ali Mahmoud, Heba Kandil, Ashraf Khalil, Mohammed Ghazal, Eric van Bogaert, Sohail Contractor, Ayman El-Baz. The Role of Radiomics and AI Technologies in the Segmentation, Detection, and Management of Hepatocellular Carcinoma. Cancers 2022; 14(24): 6123 doi: 10.3390/cancers14246123
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19 |
冰洁 李. Deep Learning in the Diagnosis and Treatment of Liver Cancer: Review and Pro-spects. Advances in Clinical Medicine 2023; 13(09): 14103 doi: 10.12677/ACM.2023.1391973
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20 |
Ruowen Li, Wenjie Qu, Qingqing Liu, Yilin Tan, Wenjing Zhang, Yiping Hao, Nan Jiang, Zhonghao Mao, Jinwen Ye, Jun Jiao, Qun Gao, Baoxia Cui, Taotao Dong. Development and validation of a deep learning survival model for cervical adenocarcinoma patients. BMC Bioinformatics 2023; 24(1) doi: 10.1186/s12859-023-05239-7
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21 |
Xiaoyuan Li, Xiaoqian Yu, Duanliang Tian, Yiran Liu, Ding Li. Exploring and validating the prognostic value of pathomics signatures and genomics in patients with cutaneous melanoma based on bioinformatics and deep learning. Medical Physics 2023; 50(11): 7049 doi: 10.1002/mp.16748
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22 |
B. Lakshmipriya, Biju Pottakkat, G. Ramkumar. Deep learning techniques in liver tumour diagnosis using CT and MR imaging - A systematic review. Artificial Intelligence in Medicine 2023; 141: 102557 doi: 10.1016/j.artmed.2023.102557
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23 |
Gang Peng, Xiaojing Cao, Xiaoyu Huang, Xiang Zhou. Radiomics and machine learning based on preoperative MRI for predicting extrahepatic metastasis in hepatocellular carcinoma patients treated with transarterial chemoembolization. European Journal of Radiology Open 2024; 12: 100551 doi: 10.1016/j.ejro.2024.100551
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24 |
Quirino Lai, Samuele lesari, Jan P. Lerut. The impact of biological features for a better prediction of posttransplant hepatocellular cancer recurrence. Current Opinion in Organ Transplantation 2022; 27(4): 305 doi: 10.1097/MOT.0000000000000955
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25 |
Arian Mansur, Andrea Vrionis, Jonathan P. Charles, Kayesha Hancel, John C. Panagides, Farzad Moloudi, Shams Iqbal, Dania Daye. The Role of Artificial Intelligence in the Detection and Implementation of Biomarkers for Hepatocellular Carcinoma: Outlook and Opportunities. Cancers 2023; 15(11): 2928 doi: 10.3390/cancers15112928
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26 |
Feifei Lu, Yao Meng, Xiaoting Song, Xiaotong Li, Zhuang Liu, Chunru Gu, Xiaojie Zheng, Yi Jing, Wei Cai, Kanokwan Pinyopornpanish, Andrea Mancuso, Fernando Gomes Romeiro, Nahum Méndez-Sánchez, Xingshun Qi. Artificial Intelligence in Liver Diseases: Recent Advances. Advances in Therapy 2024; 41(3): 967 doi: 10.1007/s12325-024-02781-5
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27 |
Alexandru Blidisel, Iasmina Marcovici, Dorina Coricovac, Florin Hut, Cristina Adriana Dehelean, Octavian Marius Cretu. Experimental Models of Hepatocellular Carcinoma—A Preclinical Perspective. Cancers 2021; 13(15): 3651 doi: 10.3390/cancers13153651
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28 |
Chrysanthos D Christou, Georgios Tsoulfas. Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology. World Journal of Gastroenterology 2021; 27(37): 6191-6223 doi: 10.3748/wjg.v27.i37.6191
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29 |
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
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30 |
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
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31 |
Qingguo Mo, Wenjing Li, Lin Liu, Zhidong Hao, Shengjun Jia, Yongsheng Duo. A nomogram based on 4-lncRNAs signature for improving prognostic prediction of hepatocellular carcinoma. Clinical and Translational Oncology 2023; 26(2): 375 doi: 10.1007/s12094-023-03244-z
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32 |
Jian Zhang, Shenglan Huang, Yongkang Xu, Jianbing Wu. Diagnostic Accuracy of Artificial Intelligence Based on Imaging Data for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.763842
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33 |
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
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