For: | Li B, Cai SL, Tan WM, Li JC, Yalikong A, Feng XS, Yu HH, Lu PX, Feng Z, Yao LQ, Zhou PH, Yan B, Zhong YS. Comparative study on artificial intelligence systems for detecting early esophageal squamous cell carcinoma between narrow-band and white-light imaging. World J Gastroenterol 2021; 27(3): 281-293 [PMID: 33519142 DOI: 10.3748/wjg.v27.i3.281] |
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URL: | https://www.wjgnet.com/1007-9327/full/v27/i3/281.htm |
Number | Citing Articles |
1 |
浩 王. Research Progress on Artificial Intelligence-Assisted Endoscopic Identification of Esophageal Cancer. Advances in Clinical Medicine 2024; 14(09): 715 doi: 10.12677/acm.2024.1492521
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2 |
Sayaka Nagao, Yasuhiro Tani, Junichi Shibata, Yosuke Tsuji, Tomohiro Tada, Ryu Ishihara, Mitsuhiro Fujishiro. Implementation of artificial intelligence in upper gastrointestinal endoscopy. DEN Open 2022; 2(1) doi: 10.1002/deo2.72
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3 |
Qian-Qian Meng, Ye Gao, Han Lin, Tian-Jiao Wang, Yan-Rong Zhang, Jian Feng, Zhao-Shen Li, Lei Xin, Luo-Wei Wang. Application of an artificial intelligence system for endoscopic diagnosis of superficial esophageal squamous cell carcinoma. World Journal of Gastroenterology 2022; 28(37): 5483-5493 doi: 10.3748/wjg.v28.i37.5483
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4 |
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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5 |
Xiang-Lei Yuan, Xian-Hui Zeng, Wei Liu, Yi Mou, Wan-Hong Zhang, Zheng-Duan Zhou, Xin Chen, Yan-Xing Hu, Bing Hu. Artificial intelligence for detecting and delineating the extent of superficial esophageal squamous cell carcinoma and precancerous lesions under narrow-band imaging (with video). Gastrointestinal Endoscopy 2023; 97(4): 664 doi: 10.1016/j.gie.2022.12.003
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6 |
Yongkang Tao, Long Fang, Geng Qin, Yingying Xu, Shuang Zhang, Xiangrong Zhang, Shiyu Du. Efficiency of endoscopic artificial intelligence in the diagnosis of early esophageal cancer. Thoracic Cancer 2024; 15(16): 1296 doi: 10.1111/1759-7714.15261
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7 |
Paul T Kröner, Megan ML Engels, Benjamin S Glicksberg, Kipp W Johnson, Obaie Mzaik, Jeanin E van Hooft, Michael B Wallace, Hashem B El-Serag, Chayakrit Krittanawong. Artificial intelligence in gastroenterology: A state-of-the-art review. World Journal of Gastroenterology 2021; 27(40): 6794-6824 doi: 10.3748/wjg.v27.i40.6794
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8 |
Hemant Goyal, Syed A. A. Sherazi, Rupinder Mann, Zainab Gandhi, Abhilash Perisetti, Muhammad Aziz, Saurabh Chandan, Jonathan Kopel, Benjamin Tharian, Neil Sharma, Nirav Thosani. Scope of Artificial Intelligence in Gastrointestinal Oncology. Cancers 2021; 13(21): 5494 doi: 10.3390/cancers13215494
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9 |
Min Liang, Chunhong Xu, Xinyan Zhang, Zongwang Zhang, Junli Cao. Effect of anesthesia assistance on the detection rate of precancerous lesions and early esophageal squamous cell cancer in esophagogastroduodenoscopy screening: A retrospective study based on propensity score matching. Frontiers in Medicine 2023; 10 doi: 10.3389/fmed.2023.1039979
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10 |
Md. Mohaimenul Islam, Tahmina Nasrin Poly, Bruno Andreas Walther, Chih-Yang Yeh, Shabbir Seyed-Abdul, Yu-Chuan (Jack) Li, Ming-Chin Lin. Deep Learning for the Diagnosis of Esophageal Cancer in Endoscopic Images: A Systematic Review and Meta-Analysis. Cancers 2022; 14(23): 5996 doi: 10.3390/cancers14235996
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11 |
Yuwei Pan, Lanying He, Weiqing Chen, Yongtao Yang. The current state of artificial intelligence in endoscopic diagnosis of early esophageal squamous cell carcinoma. Frontiers in Oncology 2023; 13 doi: 10.3389/fonc.2023.1198941
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12 |
Jun-Qi Zhang, Jun-Jie Mi, Rong Wang. Application of convolutional neural network-based endoscopic imaging in esophageal cancer or high-grade dysplasia: A systematic review and meta-analysis. World Journal of Gastrointestinal Oncology 2023; 15(11): 1998-2016 doi: 10.4251/wjgo.v15.i11.1998
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13 |
Suigu Tang, Xiaoyuan Yu, Chak Fong Cheang, Xiaoyu Ji, Hon Ho Yu, I Cheong Choi. CLELNet: A continual learning network for esophageal lesion analysis on endoscopic images. Computer Methods and Programs in Biomedicine 2023; 231: 107399 doi: 10.1016/j.cmpb.2023.107399
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14 |
Pierfrancesco Visaggi, Nicola de Bortoli, Brigida Barberio, Vincenzo Savarino, Roberto Oleas, Emma M. Rosi, Santino Marchi, Mentore Ribolsi, Edoardo Savarino. Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases. Journal of Clinical Gastroenterology 2022; 56(1): 23 doi: 10.1097/MCG.0000000000001629
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15 |
De Luo, Fei Kuang, Juan Du, Mengjia Zhou, Xiangdong Liu, Xinchen Luo, Yong Tang, Bo Li, Song Su. Artificial Intelligence–Assisted Endoscopic Diagnosis of Early Upper Gastrointestinal Cancer: A Systematic Review and Meta-Analysis. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.855175
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16 |
Ji-Han Qi, Shi-Ling Huang, Shi-Zhu Jin. Novel milestones for early esophageal carcinoma: From bench to bed. World Journal of Gastrointestinal Oncology 2024; 16(4): 1104-1118 doi: 10.4251/wjgo.v16.i4.1104
Abstract(239) |
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17 |
Charalampos Theocharopoulos, Spyridon Davakis, Dimitrios C. Ziogas, Achilleas Theocharopoulos, Dimitra Foteinou, Adam Mylonakis, Ioannis Katsaros, Helen Gogas, Alexandros Charalabopoulos. Deep Learning for Image Analysis in the Diagnosis and Management of Esophageal Cancer. Cancers 2024; 16(19): 3285 doi: 10.3390/cancers16193285
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18 |
Wan-Yue Zhang, Yong-Jian Chang, Rui-Hua Shi. Artificial intelligence enhances the management of esophageal squamous cell carcinoma in the precision oncology era. World Journal of Gastroenterology 2024; 30(39): 4267-4280 doi: 10.3748/wjg.v30.i39.4267
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19 |
Hari Mohan Rai, Joon Yoo, Abdul Razaque. Comparative analysis of machine learning and deep learning models for improved cancer detection: A comprehensive review of recent advancements in diagnostic techniques. Expert Systems with Applications 2024; 255: 124838 doi: 10.1016/j.eswa.2024.124838
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20 |
Ming-Wun Wong, Benjamin D. Rogers, Min-Xiang Liu, Wei-Yi Lei, Tso-Tsai Liu, Chih-Hsun Yi, Jui-Sheng Hung, Shu-Wei Liang, Chiu-Wang Tseng, Jen-Hung Wang, Ping-An Wu, Chien-Lin Chen. Application of Artificial Intelligence in Measuring Novel pH-Impedance Metrics for Optimal Diagnosis of GERD. Diagnostics 2023; 13(5): 960 doi: 10.3390/diagnostics13050960
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21 |
T. A. Sadulaeva, L. A. Edilgireeva, M. B. Bimurzaeva, A. O. Morozov. Use of artificial intelligence in diagnostic cystoscopy of bladder cancer. Cancer Urology 2023; 19(2): 146 doi: 10.17650/1726-9776-2023-19-2-148-152
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22 |
Shaleen Vasavada, Sharmila Anandasabapathy. Image Enhanced Endoscopy in Esophageal Squamous Cell Carcinoma. Foregut: The Journal of the American Foregut Society 2024; 4(1): 82 doi: 10.1177/26345161231211752
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23 |
Pierfrancesco Visaggi, Brigida Barberio, Dario Gregori, Danila Azzolina, Matteo Martinato, Cesare Hassan, Prateek Sharma, Edoardo Savarino, Nicola de Bortoli. Systematic review with meta‐analysis: artificial intelligence in the diagnosis of oesophageal diseases. Alimentary Pharmacology & Therapeutics 2022; 55(5): 528 doi: 10.1111/apt.16778
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24 |
Silvia Pecere, Sebastian Manuel Milluzzo, Gianluca Esposito, Emanuele Dilaghi, Andrea Telese, Leonardo Henry Eusebi. Applications of Artificial Intelligence for the Diagnosis of Gastrointestinal Diseases. Diagnostics 2021; 11(9): 1575 doi: 10.3390/diagnostics11091575
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25 |
Nadia Guidozzi, Nainika Menon, Swathikan Chidambaram, Sheraz Rehan Markar. The role of artificial intelligence in the endoscopic diagnosis of esophageal cancer: a systematic review and meta-analysis. Diseases of the Esophagus 2023; 36(12) doi: 10.1093/dote/doad048
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26 |
Jonathan S Galati, Robert J Duve, Matthew O'Mara, Seth A Gross. Artificial intelligence in gastroenterology: A narrative review. Artificial Intelligence in Gastroenterology 2022; 3(5): 117-141 doi: 10.35712/aig.v3.i5.117
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