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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/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 CancerDisease Markers 2023; 2023: 1 doi: 10.1155/2023/5178750
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) predictionBiomedical Signal Processing and Control 2023; 85: 104908 doi: 10.1016/j.bspc.2023.104908
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 surgeryJournal of Pathology Informatics 2023; : 100360 doi: 10.1016/j.jpi.2023.100360
4
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
5
Jan Lerut. Modern technology, liver surgery and transplantationHepatobiliary & Pancreatic Diseases International 2022; 21(4): 307 doi: 10.1016/j.hbpd.2022.06.006
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 StatusAmerican Journal of Roentgenology 2022; 219(6): 985 doi: 10.2214/AJR.22.27695
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 carcinomaInfectious Agents and Cancer 2021; 16(1) doi: 10.1186/s13027-021-00393-0
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 reviewsInternational Journal of Medical Informatics 2022; 166: 104855 doi: 10.1016/j.ijmedinf.2022.104855
9
Yifan Yang, Mingquan Lin, Han Zhao, Yifan Peng, Furong Huang, Zhiyong Lu. A survey of recent methods for addressing AI fairness and bias in biomedicineJournal of Biomedical Informatics 2024; 154: 104646 doi: 10.1016/j.jbi.2024.104646
10
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
11
Yutaka Endo, Laura Alaimo, Giovanni Catalano, Odysseas P. Chatzipanagiotou, Timothy M. Pawlik. Application of artificial intelligence to hepatobiliary cancer clinical outcomes researchArtificial Intelligence Surgery 2024; 4(2): 59 doi: 10.20517/ais.2024.09
12
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
13
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
14
Quirino Lai, Simona Parisse, Stefano Ginanni Corradini, Flaminia Ferri, Konstantina Kolovou, Pasquale Campagna, Fabio Melandro, Gianluca Mennini, Manuela Merli, Massimo Rossi. Evolution of transplant oncology indications: a single-institution experience over 40 yearsUpdates in Surgery 2024; 76(3): 911 doi: 10.1007/s13304-024-01827-1
15
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
16
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
17
Amene Saghazadeh, Nima Rezaei. Handbook of Cancer and Immunology2023; : 1 doi: 10.1007/978-3-030-80962-1_309-1
18
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 2023; 70(S4) doi: 10.1002/pbc.29965
19
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-AnalysisCancers 2023; 15(23): 5701 doi: 10.3390/cancers15235701
20
Afrouz Ataei, Jun Deng, Wazir Muhammad. Liver cancer risk quantification through an artificial neural network based on personal health dataActa Oncologica 2023; 62(5): 495 doi: 10.1080/0284186X.2023.2213445
21
Abdullah Altaf, Yutaka Endo, Muhammad M. Munir, Muhammad Muntazir M. Khan, Zayed Rashid, Mujtaba Khalil, Alfredo Guglielmi, Francesca Ratti, Hugo Marques, François Cauchy, Vincent Lam, George Poultsides, Minoru Kitago, Irinel Popescu, Guillaume Martel, Ana Gleisner, Tom Hugh, Feng Shen, Itaru Endo, Timothy M. Pawlik. Impact of an artificial intelligence based model to predict non-transplantable recurrence among patients with hepatocellular carcinomaHPB 2024;  doi: 10.1016/j.hpb.2024.05.006
22
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 CarcinomaCancers 2022; 14(24): 6123 doi: 10.3390/cancers14246123
23
冰洁 李. Deep Learning in the Diagnosis and Treatment of Liver Cancer: Review and Pro-spectsAdvances in Clinical Medicine 2023; 13(09): 14103 doi: 10.12677/ACM.2023.1391973
24
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 patientsBMC Bioinformatics 2023; 24(1) doi: 10.1186/s12859-023-05239-7
25
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 learningMedical Physics 2023; 50(11): 7049 doi: 10.1002/mp.16748
26
B. Lakshmipriya, Biju Pottakkat, G. Ramkumar. Deep learning techniques in liver tumour diagnosis using CT and MR imaging - A systematic reviewArtificial Intelligence in Medicine 2023; 141: 102557 doi: 10.1016/j.artmed.2023.102557
27
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 chemoembolizationEuropean Journal of Radiology Open 2024; 12: 100551 doi: 10.1016/j.ejro.2024.100551
28
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
29
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 OpportunitiesCancers 2023; 15(11): 2928 doi: 10.3390/cancers15112928
30
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 AdvancesAdvances in Therapy 2024;  doi: 10.1007/s12325-024-02781-5
31
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
32
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
33
Riccardo DE ROBERTIS, Flavio SPOTO, Francesca PASQUAZZO, Mirko D’ONOFRIO. Clinical applications of radiomics and artificial intelligence: prognostic stratification and response to treatmentJournal of Radiological Review 2023; 10(3) doi: 10.23736/S2723-9284.23.00245-9
34
Jingyang Zhou, Runmeng Cui, Lin Lin. A Systematic Review of the Application of Computational Technology in MicrotiaJournal of Craniofacial Surgery 2024;  doi: 10.1097/SCS.0000000000010210
35
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
36
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 carcinomaClinical and Translational Oncology 2023; 26(2): 375 doi: 10.1007/s12094-023-03244-z
37
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
38
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