BPG is committed to discovery and dissemination of knowledge
Cited by in CrossRef
For: Azer SA. Deep learning with convolutional neural networks for identification of liver masses and hepatocellular carcinoma: A systematic review. World J Gastrointest Oncol 2019; 11(12): 1218-1230 [PMID: 31908726 DOI: 10.4251/wjgo.v11.i12.1218]
URL: https://www.wjgnet.com/1948-5204/full/v11/i12/1218.htm
Number Citing Articles
1
Anna Castaldo, Davide Raffaele De Lucia, Giuseppe Pontillo, Marco Gatti, Sirio Cocozza, Lorenzo Ugga, Renato Cuocolo. State of the Art in Artificial Intelligence and Radiomics in Hepatocellular CarcinomaDiagnostics 2021; 11(7): 1194 doi: 10.3390/diagnostics11071194
2
Nurbubu Moldogazieva, Innokenty Mokhosoev, Sergey Zavadskiy, Alexander Terentiev. Proteomic Profiling and Artificial Intelligence for Hepatocellular Carcinoma Translational MedicineBiomedicines 2021; 9(2): 159 doi: 10.3390/biomedicines9020159
3
Nelson S Yee. Machine intelligence for precision oncologyWorld Journal of Translational Medicine 2021; 9(1): 1-10 doi: 10.5528/wjtm.v9.i1.1
4
George E Fowler, Rhiannon C Macefield, Conor Hardacre, Mark P Callaway, Neil J Smart, Natalie S Blencowe. Artificial intelligence as a diagnostic aid in cross-sectional radiological imaging of the abdominopelvic cavity: a protocol for a systematic reviewBMJ Open 2021; 11(10): e054411 doi: 10.1136/bmjopen-2021-054411
5
Joseph C Ahn, Touseef Ahmad Qureshi, Amit G Singal, Debiao Li, Ju-Dong Yang. Deep learning in hepatocellular carcinoma: Current status and future perspectivesWorld Journal of Hepatology 2021; 13(12): 2039-2051 doi: 10.4254/wjh.v13.i12.2039
6
Ching-Juei Yang, Chien-Kuo Wang, Yu-Hua Dean Fang, Jing-Yao Wang, Fong-Chin Su, Hong-Ming Tsai, Yih-Jyh Lin, Hung-Wen Tsai, Lee-Ren Yeh, Khanh N.Q. Le. Clinical application of mask region-based convolutional neural network for the automatic detection and segmentation of abnormal liver density based on hepatocellular carcinoma computed tomography datasetsPLOS ONE 2021; 16(8): e0255605 doi: 10.1371/journal.pone.0255605
7
Miguel Jiménez Pérez, Rocío González Grande. Application of artificial intelligence in the diagnosis and treatment of hepatocellular carcinoma: A reviewWorld Journal of Gastroenterology 2020; 26(37): 5617-5628 doi: 10.3748/wjg.v26.i37.5617
8
Delia Mitrea, Radu Badea, Paulina Mitrea, Stelian Brad, Sergiu Nedevschi. Hepatocellular Carcinoma Automatic Diagnosis within CEUS and B-Mode Ultrasound Images Using Advanced Machine Learning MethodsSensors 2021; 21(6): 2202 doi: 10.3390/s21062202
9
Seung-seob Kim, Dong Ho Lee, Min Woo Lee, So Yeon Kim, Jaeseung Shin, Jin-Young Choi, Byoung Wook Choi. Construction of a Standard Dataset for Liver Tumors for Testing the Performance and Safety of Artificial Intelligence-Based Clinical Decision Support SystemsJournal of the Korean Society of Radiology 2021; 82(5): 1196 doi: 10.3348/jksr.2020.0177
10
Efficient Local Cloud-Based Solution for Liver Cancer Detection Using Deep LearningInternational Journal of Cloud Applications and Computing 2022; 12(1): 1 doi: 10.4018/IJCAC.2022010109
11
Donlapark Ponnoprat, Papangkorn Inkeaw, Jeerayut Chaijaruwanich, Patrinee Traisathit, Patumrat Sripan, Nakarin Inmutto, Wittanee Na Chiangmai, Donsuk Pongnikorn, Imjai Chitapanarux. Classification of hepatocellular carcinoma and intrahepatic cholangiocarcinoma based on multi-phase CT scansMedical & Biological Engineering & Computing 2020; 58(10): 2497 doi: 10.1007/s11517-020-02229-2
12
Saleh Alaraimi, Kenneth E. Okedu, Hugo Tianfield, Richard Holden, Omair Uthmani. Transfer learning networks with skip connections for classification of brain tumorsInternational Journal of Imaging Systems and Technology 2021; 31(3): 1564 doi: 10.1002/ima.22546
13
Dinh‐Van Phan, Chien‐Lung Chan, Ai‐Hsien Adams Li, Ting‐Ying Chien, Van‐Chuc Nguyen. Liver cancer prediction in a viral hepatitis cohort: A deep learning approachInternational Journal of Cancer 2020; 147(10): 2871 doi: 10.1002/ijc.33245
14
Yan Zhu, Aihong Yu, Huan Rong, Dongqing Wang, Yuqing Song, Zhe Liu, Victor S. Sheng. Multi-Resolution Image Segmentation Based on a Cascaded U-ADenseNet for the Liver and TumorsJournal of Personalized Medicine 2021; 11(10): 1044 doi: 10.3390/jpm11101044
15
Song-Toan Tran, Ching-Hwa Cheng, Don-Gey Liu. A Multiple Layer U-Net, Un-Net, for Liver and Liver Tumor Segmentation in CTIEEE Access 2021; 9: 3752 doi: 10.1109/ACCESS.2020.3047861
16
Jonathan R. Dillman, Elan Somasundaram, Samuel L. Brady, Lili He. Current and emerging artificial intelligence applications for pediatric abdominal imagingPediatric Radiology 2021;  doi: 10.1007/s00247-021-05057-0
17
Lekshmi Kalinathan, Deepika Sivasankaran, Janet Reshma Jeyasingh, Amritha Sennappa Sudharsan, Hareni Marimuthu. Hepatocellular Carcinoma - Challenges and Opportunities of a Multidisciplinary Approach [Working Title]2021;  doi: 10.5772/intechopen.99841
18
Rayyan Azam Khan, Yigang Luo, Fang-Xiang Wu. Machine learning based liver disease diagnosis: A systematic reviewNeurocomputing 2022; 468: 492 doi: 10.1016/j.neucom.2021.08.138
19
Kamyab Keshtkar, Abbas Keshtkar, Alireza Safarpour. Classifying colorectal cancer or colorectal polyps in endoscopic setting using convolutional neural network: protocol for a systematic review and meta-analysisF1000Research 2020; 9: 1086 doi: 10.12688/f1000research.25548.1
20
Quirino Lai, Gabriele Spoletini, Gianluca Mennini, Zoe Larghi Laureiro, Diamantis I Tsilimigras, Timothy Michael Pawlik, Massimo Rossi. Prognostic role of artificial intelligence among patients with hepatocellular cancer: A systematic reviewWorld Journal of Gastroenterology 2020; 26(42): 6679-6688 doi: 10.3748/wjg.v26.i42.6679
21
Xue-Qin Gong, Yun-Yun Tao, Yao–Kun Wu, Ning Liu, Xi Yu, Ran Wang, Jing Zheng, Nian Liu, Xiao-Hua Huang, Jing-Dong Li, Gang Yang, Xiao-Qin Wei, Lin Yang, Xiao-Ming Zhang. Progress of MRI Radiomics in Hepatocellular CarcinomaFrontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.698373
22
Shi Feng, Xiaotian Yu, Wenjie Liang, Xuejie Li, Weixiang Zhong, Wanwan Hu, Han Zhang, Zunlei Feng, Mingli Song, Jing Zhang, Xiuming Zhang. Development of a Deep Learning Model to Assist With Diagnosis of Hepatocellular CarcinomaFrontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.762733
23
Francesco Fiz, Luca Viganò, Nicolò Gennaro, Guido Costa, Ludovico La Bella, Alexandra Boichuk, Lara Cavinato, Martina Sollini, Letterio S. Politi, Arturo Chiti, Guido Torzilli. Radiomics of Liver Metastases: A Systematic ReviewCancers 2020; 12(10): 2881 doi: 10.3390/cancers12102881
24
Precilla S Daisy, T. S. Anitha. Can artificial intelligence overtake human intelligence on the bumpy road towards glioma therapy?Medical Oncology 2021; 38(5) doi: 10.1007/s12032-021-01500-2
25
Uli Fehrenbach, Siyi Xin, Alexander Hartenstein, Timo Alexander Auer, Franziska Dräger, Konrad Froböse, Henning Jann, Martina Mogl, Holger Amthauer, Dominik Geisel, Timm Denecke, Bertram Wiedenmann, Tobias Penzkofer. Automatized Hepatic Tumor Volume Analysis of Neuroendocrine Liver Metastases by Gd-EOB MRI—A Deep-Learning Model to Support Multidisciplinary Cancer Conference Decision-MakingCancers 2021; 13(11): 2726 doi: 10.3390/cancers13112726
26
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
27
Yogesh Kumar, Surbhi Gupta, Ruchi Singla, Yu-Chen Hu. A Systematic Review of Artificial Intelligence Techniques in Cancer Prediction and DiagnosisArchives of Computational Methods in Engineering 2021;  doi: 10.1007/s11831-021-09648-w
28
Wenqi Shi, Sichi Kuang, Sue Cao, Bing Hu, Sidong Xie, Simin Chen, Yinan Chen, Dashan Gao, Yunqiang Chen, Yajing Zhu, Hanxi Zhang, Hui Liu, Meng Ye, Claude B. Sirlin, Jin Wang. Deep learning assisted differentiation of hepatocellular carcinoma from focal liver lesions: choice of four-phase and three-phase CT imaging protocolAbdominal Radiology 2020; 45(9): 2688 doi: 10.1007/s00261-020-02485-8
29
Qi Feng, Han Chen, Ruohan Jiang. Analysis of early warning of corporate financial risk via deep learning artificial neural networkMicroprocessors and Microsystems 2021; 87: 104387 doi: 10.1016/j.micpro.2021.104387
30
Khaled Bousabarah, Brian Letzen, Jonathan Tefera, Lynn Savic, Isabel Schobert, Todd Schlachter, Lawrence H. Staib, Martin Kocher, Julius Chapiro, MingDe Lin. Automated detection and delineation of hepatocellular carcinoma on multiphasic contrast-enhanced MRI using deep learningAbdominal Radiology 2021; 46(1): 216 doi: 10.1007/s00261-020-02604-5