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Cited by in CrossRef
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]
URL: https://www.wjgnet.com/1948-5182/full/v26/i42/6679.htm
Number Citing Articles
1
Haopeng Kuang, Zhongwei Yang, Xukun Zhang, Shunli Wang, Lihua Zhang. A Review of Artificial Intelligence in Preoperative Clinical Staging of Liver Cancer2021 International Conference on Networking Systems of AI (INSAI) 2021; : 69 doi: 10.1109/INSAI54028.2021.00024
2
Jan Lerut. Modern technology, liver surgery and transplantationHepatobiliary & Pancreatic Diseases International 2022; 21(4): 307 doi: 10.1016/j.hbpd.2022.06.006
3
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 StatusAmerican Journal of Roentgenology 2022; 219(6): 985 doi: 10.2214/AJR.22.27695
4
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 carcinomaInfectious Agents and Cancer 2021; 16(1) doi: 10.1186/s13027-021-00393-0
5
Quirino Lai, Samuele lesari, Jan P. Lerut. The impact of biological features for a better prediction of posttransplant hepatocellular cancer recurrenceCurrent Opinion in Organ Transplantation 2022; 27(4): 305 doi: 10.1097/MOT.0000000000000955
6
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 reviewsInternational Journal of Medical Informatics 2022; 166: 104855 doi: 10.1016/j.ijmedinf.2022.104855
7
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
8
Sachin C Sarode, Nilesh Kumar Sharma, Gargi Sarode. A critical appraisal on cancer prognosis and artificial intelligenceFuture Oncology 2022; 18(13): 1531 doi: 10.2217/fon-2021-1528
9
Alexandru Blidisel, Iasmina Marcovici, Dorina Coricovac, Florin Hut, Cristina Adriana Dehelean, Octavian Marius Cretu. Experimental Models of Hepatocellular Carcinoma—A Preclinical PerspectiveCancers 2021; 13(15): 3651 doi: 10.3390/cancers13153651
10
Chrysanthos D Christou, Georgios Tsoulfas. Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatologyWorld Journal of Gastroenterology 2021; 27(37): 6191-6223 doi: 10.3748/wjg.v27.i37.6191
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 cancersInfectious Agents and Cancer 2022; 17(1) doi: 10.1186/s13027-022-00422-6
12
Vinícius Remus Ballotin, Lucas Goldmann Bigarella, John Soldera, Jonathan Soldera. Deep learning applied to the imaging diagnosis of hepatocellular carcinomaArtificial Intelligence in Gastrointestinal Endoscopy 2021; 2(4): 127-135 doi: 10.37126/aige.v2.i4.127
13
Aleksander Krasowski, Joachim Krois, Adelheid Kuhlmey, Hendrik Meyer-Lueckel, Falk Schwendicke. Predicting mortality in the very old: a machine learning analysis on claims dataScientific Reports 2022; 12(1) doi: 10.1038/s41598-022-21373-3
14
Yun Qin, Li-Hua Zhu, Wei Zhao, Jun-Jie Wang, Hao Wang. Review of Radiomics- and Dosiomics-based Predicting Models for Rectal CancerFrontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.913683
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 PaperPediatric Blood & Cancer 2022;  doi: 10.1002/pbc.29965
16
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-AnalysisFrontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.763842
17
Francesca Romana Ponziani, Edoardo G. Giannini, Quirino Lai. Machine learning and biomarkers in hepatocellular carcinoma: The future is nowLiver Cancer International 2022; 3(3): 111 doi: 10.1002/lci2.67