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] |
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URL: | https://www.wjgnet.com/1948-5190/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 Gastrointestinaltrakts. Die Onkologie 2023; 29(6): 515 doi: 10.1007/s00761-023-01318-9
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2 |
Kiran Raj M, Jyotsana Priyadarshani, Pratyaksh Karan, Saumyadwip Bandyopadhyay, Soumya Bhattacharya, Suman Chakraborty. Bio-inspired microfluidics: A review. Biomicrofluidics 2023; 17(5) doi: 10.1063/5.0161809
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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 Images. Bioengineering 2023; 10(11): 1288 doi: 10.3390/bioengineering10111288
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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 Studies. Cureus 2021; doi: 10.7759/cureus.15447
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5 |
Qing Li, Bing-Rong Liu. Application of artificial intelligence-assisted endoscopic detection of early esophageal cancer. World Chinese Journal of Digestology 2021; 29(24): 1389 doi: 10.11569/wcjd.v29.i24.1389
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6 |
Dong Huang, Xiaopan Xu, Peng Du, Yuefei Feng, Xi Zhang, Hongbing Lu, Yang Liu. Radiomics-based T-staging of hollow organ cancers. Frontiers in Oncology 2023; 13 doi: 10.3389/fonc.2023.1191519
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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 surgeon. Current Opinion in Oncology 2021; 33(4): 353 doi: 10.1097/CCO.0000000000000751
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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 Disease. Journal of Medical and Biological Engineering 2021; 41(4): 504 doi: 10.1007/s40846-021-00608-0
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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 Imaging. Cancers 2022; 14(17): 4292 doi: 10.3390/cancers14174292
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10 |
Lingyu Wang, Ning Ding, Pengfei Zuo, Xuenan Wang, B Karunakara Rai. Application and Challenges of Artificial Intelligence in Medical Imaging. 2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) 2022; : 1 doi: 10.1109/ICKECS56523.2022.10059898
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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 study. Medical & Biological Engineering & Computing 2023; 61(7): 1631 doi: 10.1007/s11517-023-02777-3
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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 junction. Journal of Digestive Diseases 2023; 24(2): 98 doi: 10.1111/1751-2980.13167
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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 Model. Computational Intelligence and Neuroscience 2022; 2022: 1 doi: 10.1155/2022/4629178
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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 Medicine. Diagnostics 2023; 13(18): 2992 doi: 10.3390/diagnostics13182992
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15 |
Thifhelimbilu Luvhengo, Thulo Molefi, Demetra Demetriou, Rodney Hull, Zodwa Dlamini. Artificial Intelligence and Precision Oncology. 2023; : 49 doi: 10.1007/978-3-031-21506-3_3
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16 |
Yu Yang, Yu-Xuan Li, Ren-Qi Yao, Xiao-Hui Du, Chao Ren. Artificial intelligence in small intestinal diseases: Application and prospects. World Journal of Gastroenterology 2021; 27(25): 3734-3747 doi: 10.3748/wjg.v27.i25.3734
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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 imaging. Biomedical Optics Express 2023; 14(8): 4383 doi: 10.1364/BOE.492635
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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 review. Annals of Medicine & Surgery 2023; 85(10): 4920 doi: 10.1097/MS9.0000000000001175
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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 analysis. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.862536
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20 |
Jennifer A. Eckhoff, Hans F. Fuchs, Ozanan R. Meireles. Anwendung von künstlicher Intelligenz in der onkologischen Chirurgie des oberen Gastrointestinaltrakts. Wiener klinisches Magazin 2023; doi: 10.1007/s00740-023-00504-0
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21 |
Rhiannon McShane, Swati Arya, Alan J. Stewart, Peter D. Caie, Mark Bates. Prognostic features of the tumour microenvironment in oesophageal adenocarcinoma. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer 2021; 1876(2): 188598 doi: 10.1016/j.bbcan.2021.188598
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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 approach. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.887841
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23 |
JunHo Lee, Hanna Lee, Jun-won Chung. The Role of Artificial Intelligence in Gastric Cancer: Surgical and Therapeutic Perspectives: A Comprehensive Review. Journal of Gastric Cancer 2023; 23(3): 375 doi: 10.5230/jgc.2023.23.e31
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24 |
Magdalena Leśniewska, Rafał Patryn, Agnieszka Kopystecka, Ilona Kozioł, Julia Budzyńska. Third Eye? The Assistance of Artificial Intelligence (AI) in the Endoscopy of Gastrointestinal Neoplasms. Journal of Clinical Medicine 2023; 12(21): 6721 doi: 10.3390/jcm12216721
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25 |
Ning Li, Shi-Zhu Jin. Artificial intelligence and early esophageal cancer. Artificial Intelligence in Gastrointestinal Endoscopy 2021; 2(5): 198-210 doi: 10.37126/aige.v2.i5.198
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26 |
Noor N. Al-Mayahi, Faisel G. Mohammed. Esophageal cancer segmentation based on FCM algorithm. 2ND INTERNATIONAL CONFERENCE FOR ENGINEERING SCIENCES AND INFORMATION TECHNOLOGY (ESIT 2022): ESIT2022 Conference Proceedings 2024; 3009: 040010 doi: 10.1063/5.0185313
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27 |
Syed Wajid Aalam, Ab Basit Ahanger, Assif Assad, Muzafar A. Macha, Muzafar Rasool Bhat. Noninvasive prediction of metastasis in esophageal cancer using ensemble-based feature selection. International Journal of System Assurance Engineering and Management 2024; doi: 10.1007/s13198-024-02327-6
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28 |
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
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