BPG is committed to discovery and dissemination of knowledge
Cited by in CrossRef
For: Zhang YH, Guo LJ, Yuan XL, Hu B. Artificial intelligence-assisted esophageal cancer management: Now and future. World J Gastroenterol 2020; 26(35): 5256-5271 [PMID: 32994686 DOI: 10.3748/wjg.v26.i35.5256]
URL: https://www.wjgnet.com/1007-9327/full/v26/i35/5256.htm
Number Citing Articles
1
Jennifer A. Eckhoff, Hans F. Fuchs, Ozanan R. Meireles. Anwendung von künstlicher Intelligenz in der onkologischen Chirurgie des oberen GastrointestinaltraktsDie Onkologie 2023; 29(6): 515 doi: 10.1007/s00761-023-01318-9
2
Kiran Raj M, Jyotsana Priyadarshani, Pratyaksh Karan, Saumyadwip Bandyopadhyay, Soumya Bhattacharya, Suman Chakraborty. Bio-inspired microfluidics: A reviewBiomicrofluidics 2023; 17(5) doi: 10.1063/5.0161809
3
Wei Sun, Peng Li, Yan Liang, Yadong Feng, Lingxiao Zhao. Detection of Image Artifacts Using Improved Cascade Region-Based CNN for Quality Assessment of Endoscopic ImagesBioengineering 2023; 10(11): 1288 doi: 10.3390/bioengineering10111288
4
Khalid M Bhatti, Zubair S Khanzada, Matta Kuzman, Syed M Ali, Syed Y Iftikhar, Peter Small. Diagnostic Performance of Artificial Intelligence-Based Models for the Detection of Early Esophageal Cancers in Barret’s Esophagus: A Meta-Analysis of Patient-Based StudiesCureus 2021;  doi: 10.7759/cureus.15447
5
Qing Li, Bing-Rong Liu. Application of artificial intelligence-assisted endoscopic detection of early esophageal cancerWorld Chinese Journal of Digestology 2021; 29(24): 1389 doi: 10.11569/wcjd.v29.i24.1389
Abstract() |  Core Tip() |  Full Article(HTML)() | Times Cited  (0) | Total Visits (0) | Open
6
Dong Huang, Xiaopan Xu, Peng Du, Yuefei Feng, Xi Zhang, Hongbing Lu, Yang Liu. Radiomics-based T-staging of hollow organ cancersFrontiers in Oncology 2023; 13 doi: 10.3389/fonc.2023.1191519
7
Philip H. Pucher, Bas P.L. Wijnhoven, Timothy J. Underwood, John V. Reynolds, Andrew R. Davies. Thinking through the multimodal treatment of localized oesophageal cancer: the point of view of the surgeonCurrent Opinion in Oncology 2021; 33(4): 353 doi: 10.1097/CCO.0000000000000751
8
Hsu-Heng Yen, Ping-Yu Wu, Pei-Yuan Su, Chia-Wei Yang, Yang-Yuan Chen, Mei-Fen Chen, Wen-Chen Lin, Cheng-Lun Tsai, Kang-Ping Lin. Performance Comparison of the Deep Learning and the Human Endoscopist for Bleeding Peptic Ulcer DiseaseJournal of Medical and Biological Engineering 2021; 41(4): 504 doi: 10.1007/s40846-021-00608-0
9
Tsung-Jung Tsai, Arvind Mukundan, Yu-Sheng Chi, Yu-Ming Tsao, Yao-Kuang Wang, Tsung-Hsien Chen, I-Chen Wu, Chien-Wei Huang, Hsiang-Chen Wang. Intelligent Identification of Early Esophageal Cancer by Band-Selective Hyperspectral ImagingCancers 2022; 14(17): 4292 doi: 10.3390/cancers14174292
10
Lingyu Wang, Ning Ding, Pengfei Zuo, Xuenan Wang, B Karunakara Rai. Application and Challenges of Artificial Intelligence in Medical Imaging2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) 2022; : 1 doi: 10.1109/ICKECS56523.2022.10059898
11
Jinming Wang, Qigang Long, Yan Liang, Jie Song, Yadong Feng, Peng Li, Wei Sun, Lingxiao Zhao. AI-assisted identification of intrapapillary capillary loops in magnification endoscopy for diagnosing early-stage esophageal squamous cell carcinoma: a preliminary studyMedical & Biological Engineering & Computing 2023; 61(7): 1631 doi: 10.1007/s11517-023-02777-3
12
Qin Huang, Yuqing Cheng, Edward Lew, Jiong Shi, Daniel Wiener, H. Christian Weber. Patients with esophageal adenocarcinoma showed better prognosis than those with adenocarcinoma of the gastroesophageal junctionJournal of Digestive Diseases 2023; 24(2): 98 doi: 10.1111/1751-2980.13167
13
Nawaf R. Alharbe, Raafat M. Munshi, Manal M. Khayyat, Mashael M. Khayyat, Saadia Hassan Abdalaha Hamza, Abeer A. Aljohani, Laxmi Lydia. Atom Search Optimization with the Deep Transfer Learning-Driven Esophageal Cancer Classification ModelComputational Intelligence and Neuroscience 2022; 2022: 1 doi: 10.1155/2022/4629178
14
Alin-Ionut Piraianu, Ana Fulga, Carmina Liana Musat, Oana-Roxana Ciobotaru, Diana Gina Poalelungi, Elena Stamate, Octavian Ciobotaru, Iuliu Fulga. Enhancing the Evidence with Algorithms: How Artificial Intelligence Is Transforming Forensic MedicineDiagnostics 2023; 13(18): 2992 doi: 10.3390/diagnostics13182992
15
Thifhelimbilu Luvhengo, Thulo Molefi, Demetra Demetriou, Rodney Hull, Zodwa Dlamini. Artificial Intelligence and Precision Oncology2023; : 49 doi: 10.1007/978-3-031-21506-3_3
16
Yu Yang, Yu-Xuan Li, Ren-Qi Yao, Xiao-Hui Du, Chao Ren. Artificial intelligence in small intestinal diseases: Application and prospectsWorld Journal of Gastroenterology 2021; 27(25): 3734-3747 doi: 10.3748/wjg.v27.i25.3734
17
Wei-Chih Liao, Arvind Mukundan, Cleorita Sadiaza, Yu-Ming Tsao, Chien-Wei Huang, Hsiang-Chen Wang. Systematic meta-analysis of computer-aided detection to detect early esophageal cancer using hyperspectral imagingBiomedical Optics Express 2023; 14(8): 4383 doi: 10.1364/BOE.492635
18
Anmol Mohan, Zoha Asghar, Rabia Abid, Rasish Subedi, Karishma Kumari, Sushil Kumar, Koushik Majumder, Aqsa I. Bhurgri, Usha Tejwaney, Sarwan Kumar. Revolutionizing healthcare by use of artificial intelligence in esophageal carcinoma – a narrative reviewAnnals of Medicine & Surgery 2023; 85(10): 4920 doi: 10.1097/MS9.0000000000001175
19
Fang Liao, Shuangbin Yu, Ying Zhou, Benying Feng. A machine learning model predicting candidates for surgical treatment modality in patients with distant metastatic esophageal adenocarcinoma: A propensity score-matched analysisFrontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.862536
20
Jennifer A. Eckhoff, Hans F. Fuchs, Ozanan R. Meireles. Anwendung von künstlicher Intelligenz in der onkologischen Chirurgie des oberen GastrointestinaltraktsWiener klinisches Magazin 2023;  doi: 10.1007/s00740-023-00504-0
21
Rhiannon McShane, Swati Arya, Alan J. Stewart, Peter D. Caie, Mark Bates. Prognostic features of the tumour microenvironment in oesophageal adenocarcinomaBiochimica et Biophysica Acta (BBA) - Reviews on Cancer 2021; 1876(2): 188598 doi: 10.1016/j.bbcan.2021.188598
22
Qiang Shen, Hongyu Chen. A novel risk classification system based on the eighth edition of TNM frameworks for esophageal adenocarcinoma patients: A deep learning approachFrontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.887841
23
JunHo Lee, Hanna Lee, Jun-won Chung. The Role of Artificial Intelligence in Gastric Cancer: Surgical and Therapeutic Perspectives: A Comprehensive ReviewJournal of Gastric Cancer 2023; 23(3): 375 doi: 10.5230/jgc.2023.23.e31
24
Magdalena Leśniewska, Rafał Patryn, Agnieszka Kopystecka, Ilona Kozioł, Julia Budzyńska. Third Eye? The Assistance of Artificial Intelligence (AI) in the Endoscopy of Gastrointestinal NeoplasmsJournal of Clinical Medicine 2023; 12(21): 6721 doi: 10.3390/jcm12216721
25
Ning Li, Shi-Zhu Jin. Artificial intelligence and early esophageal cancerArtificial Intelligence in Gastrointestinal Endoscopy 2021; 2(5): 198-210 doi: 10.37126/aige.v2.i5.198
26
Noor N. Al-Mayahi, Faisel G. Mohammed. Esophageal cancer segmentation based on FCM algorithm2ND INTERNATIONAL CONFERENCE FOR ENGINEERING SCIENCES AND INFORMATION TECHNOLOGY (ESIT 2022): ESIT2022 Conference Proceedings 2024; 3009: 040010 doi: 10.1063/5.0185313
27
Yong Liu. Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step?World Journal of Gastroenterology 2021; 27(14): 1392-1405 doi: 10.3748/wjg.v27.i14.1392