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For: Ahn JC, Qureshi TA, Singal AG, Li D, Yang JD. Deep learning in hepatocellular carcinoma: Current status and future perspectives. World J Hepatol 2021; 13(12): 2039-2051 [PMID: 35070007 DOI: 10.4254/wjh.v13.i12.2039]
URL: https://www.wjgnet.com/1948-5182/full/v13/i12/2039.htm
Number Citing Articles
1
Jiansong Zhang, Yongjian Chen, Peizhong Liu. Automatic Recognition of Standard Liver Sections Based on Vision-Transformer2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) 2022; : 1 doi: 10.1109/ASID56930.2022.9995936
2
Naveen Bhagat, Nipun Verma, Virendra Singh. HCC prediction post SVR: Many tools yet limited generalizability!Journal of Hepatology 2022; 77(4): 1226 doi: 10.1016/j.jhep.2022.04.028
3
古门勒 乌日. Progress in the Study of Risk Factors Associated with Primary Liver CancerAdvances in Clinical Medicine 2024; 14(02): 4479 doi: 10.12677/ACM.2024.142622
4
超 陈. Research Progress of Deep Learning in Pathological Diagnosis of Liver CancerAdvances in Clinical Medicine 2023; 13(12): 18864 doi: 10.12677/ACM.2023.13122654
5
Miner Hu, Xiaojun Xia, Lichao Chen, Yunpeng Jin, Zhenhua Hu, Shudong Xia, Xudong Yao. Emerging biomolecules for practical theranostics of liver hepatocellular carcinomaAnnals of Hepatology 2023; 28(6): 101137 doi: 10.1016/j.aohep.2023.101137
6
Victor Lopez-Lopez, Zeniche Morise, Mariano Albaladejo-González, Concepción Gomez Gavara, Brian K. P. Goh, Ye Xin Koh, Sijberden Jasper Paul, Mohammed Abu Hilal, Kohei Mishima, Jaime Arthur Pirola Krürger, Paulo Herman, Alvaro Cerezuela, Roberto Brusadin, Takashi Kaizu, Juan Lujan, Fernando Rotellar, Kazuteru Monden, Mar Dalmau, Naoto Gotohda, Masashi Kudo, Akishige Kanazawa, Yutaro Kato, Hiroyuki Nitta, Satoshi Amano, Raffaele Dalla Valle, Mario Giuffrida, Masaki Ueno, Yuichiro Otsuka, Daisuke Asano, Minoru Tanabe, Osamu Itano, Takuya Minagawa, Dilmurodjon Eshmuminov, Irene Herrero, Pablo Ramírez, José A. Ruipérez-Valiente, Ricardo Robles-Campos, Go Wakabayashi. Explainable artificial intelligence prediction-based model in laparoscopic liver surgery for segments 7 and 8: an international multicenter studySurgical Endoscopy 2024;  doi: 10.1007/s00464-024-10681-6
7
Yinghui Qiu, Jingxiang Xu, Wei Liao, Yuxi Wen, Shiyue Jiang, Jiahui Wen, Chao Zhao. Suppression of hepatocellular carcinoma by Ulva lactuca ulvan via gut microbiota and metabolite interactionsJournal of Advanced Research 2023; 52: 103 doi: 10.1016/j.jare.2023.04.008
8
Mariana Michelle Ramírez-Mejía, Nahum Méndez-Sánchez. From prediction to prevention: Machine learning revolutionizes hepatocellular carcinoma recurrence monitoringWorld Journal of Gastroenterology 2024; 30(7): 631-635 doi: 10.3748/wjg.v30.i7.631
9
Vincent Sauzeau, Julien Beignet, Gérard Vergoten, Christian Bailly. Overexpressed or hyperactivated Rac1 as a target to treat hepatocellular carcinomaPharmacological Research 2022; 179: 106220 doi: 10.1016/j.phrs.2022.106220
10
Seyed Mahdi Hosseiniyan Khatibi, Farima Najjarian, Hamed Homaei Rad, Mohammadreza Ardalan, Mohammad Teshnehlab, Sepideh Zununi Vahed, Saeed Pirmoradi. Key therapeutic targets implicated at the early stage of hepatocellular carcinoma identified through machine-learning approachesScientific Reports 2023; 13(1) doi: 10.1038/s41598-023-30720-x
11
馨瑶 王. Application Value of Ultasound-Based Radiomics in the Diagnosis and Treatment of Hepatocellular CarcinomaAdvances in Clinical Medicine 2023; 13(11): 18386 doi: 10.12677/ACM.2023.13112582
12
Zhao Li, Lan Lan, Yujia Zhou, Ruoxing Li, Kenneth D. Chavin, Hua Xu, Liang Li, David J.H. Shih, W. Jim Zheng. Developing deep learning-based strategies to predict the risk of hepatocellular carcinoma among patients with nonalcoholic fatty liver disease from electronic health recordsJournal of Biomedical Informatics 2024; 152: 104626 doi: 10.1016/j.jbi.2024.104626
13
Devi Rajeev, S Dr. Remya, Dr. Anand Nayyar, Dr. Krishnanunni Nair. Predicting Hepatocellular Carcinoma Graft Survival Rate in Post Liver Transplantation Using DeepHitProcedia Computer Science 2024; 233: 307 doi: 10.1016/j.procs.2024.03.220
14
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
15
Yuri S. Velichko, Nicolo Gennaro, Meghana Karri, Matthew Antalek, Ulas Bagci. A Comprehensive Review of Deep Learning Approaches for Magnetic Resonance Imaging Liver Tumor AnalysisAdvances in Clinical Radiology 2023; 5(1): 1 doi: 10.1016/j.yacr.2023.06.001
16
Hang Sun, Huayu Yang, Yilei Mao. Personalized treatment for hepatocellular carcinoma in the era of targeted medicine and bioengineeringFrontiers in Pharmacology 2023; 14 doi: 10.3389/fphar.2023.1150151
17
Felix Schön, Aaron Kieslich, Heiner Nebelung, Carina Riediger, Ralf-Thorsten Hoffmann, Alex Zwanenburg, Steffen Löck, Jens-Peter Kühn. Comparative analysis of radiomics and deep-learning algorithms for survival prediction in hepatocellular carcinomaScientific Reports 2024; 14(1) doi: 10.1038/s41598-023-50451-3
18
Pablo Martínez-Blanco, Miguel Suárez, Sergio Gil-Rojas, Ana María Torres, Natalia Martínez-García, Pilar Blasco, Miguel Torralba, Jorge Mateo. Prognostic Factors for Mortality in Hepatocellular Carcinoma at Diagnosis: Development of a Predictive Model Using Artificial IntelligenceDiagnostics 2024; 14(4): 406 doi: 10.3390/diagnostics14040406
19
Jiansong Zhang, Yongjian Chen, Pan Zeng, Yao Liu, Yong Diao, Peizhong Liu. Ultra-Attention: Automatic Recognition of Liver Ultrasound Standard Sections Based on Visual Attention Perception StructuresUltrasound in Medicine & Biology 2023; 49(4): 1007 doi: 10.1016/j.ultrasmedbio.2022.12.016