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Cited by in F6Publishing
For: Song EM, Park B, Ha CA, Hwang SW, Park SH, Yang DH, Ye BD, Myung SJ, Yang SK, Kim N, Byeon JS. Endoscopic diagnosis and treatment planning for colorectal polyps using a deep-learning model. Sci Rep. 2020;10:30. [PMID: 31913337 DOI: 10.1038/s41598-019-56697-0] [Cited by in Crossref: 17] [Cited by in F6Publishing: 17] [Article Influence: 8.5] [Reference Citation Analysis]
Number Citing Articles
1 El-Nakeep S, El-Nakeep M. Artificial intelligence for cancer detection in upper gastrointestinal endoscopy, current status, and future aspirations. Artif Intell Gastroenterol 2021; 2(5): 124-132 [DOI: 10.35712/aig.v2.i5.124] [Reference Citation Analysis]
2 Fan D, Hou J, Zhang T, Ye Y. Evaluation of narrow band imaging for diagnosis of unilateral nasal lesions. Clin Otolaryngol 2021;46:388-94. [PMID: 33320431 DOI: 10.1111/coa.13688] [Reference Citation Analysis]
3 Okagawa Y, Abe S, Yamada M, Oda I, Saito Y. Artificial Intelligence in Endoscopy. Dig Dis Sci 2021. [PMID: 34155567 DOI: 10.1007/s10620-021-07086-z] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Owais M, Arsalan M, Mahmood T, Kang JK, Park KR. Automated Diagnosis of Various Gastrointestinal Lesions Using a Deep Learning-Based Classification and Retrieval Framework With a Large Endoscopic Database: Model Development and Validation. J Med Internet Res 2020;22:e18563. [PMID: 33242010 DOI: 10.2196/18563] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Kim JH, Nam SJ, Park SC. Usefulness of artificial intelligence in gastric neoplasms. World J Gastroenterol 2021; 27(24): 3543-3555 [PMID: 34239268 DOI: 10.3748/wjg.v27.i24.3543] [Reference Citation Analysis]
6 Jin HY, Zhang M, Hu B. Techniques to integrate artificial intelligence systems with medical information in gastroenterology. Artif Intell Gastrointest Endosc 2020; 1(1): 19-27 [DOI: 10.37126/aige.v1.i1.19] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
7 Taghiakbari M, Mori Y, von Renteln D. Artificial intelligence-assisted colonoscopy: A review of current state of practice and research. World J Gastroenterol 2021; 27(47): 8103-8122 [DOI: 10.3748/wjg.v27.i47.8103] [Reference Citation Analysis]
8 Zhuang H, Bao A, Tan Y, Wang H, Xie Q, Qiu M, Xiong W, Liao F. Application and prospect of artificial intelligence in digestive endoscopy. Expert Rev Gastroenterol Hepatol 2021;:1-11. [PMID: 34937459 DOI: 10.1080/17474124.2022.2020646] [Reference Citation Analysis]
9 Li S, Zeng Y, Chapman WC Jr, Erfanzadeh M, Nandy S, Mutch M, Zhu Q. Adaptive Boosting (AdaBoost)-based multiwavelength spatial frequency domain imaging and characterization for ex vivo human colorectal tissue assessment. J Biophotonics 2020;13:e201960241. [PMID: 32125775 DOI: 10.1002/jbio.201960241] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
10 Correia FP, Lourenço LC. Artificial intelligence application in diagnostic gastrointestinal endoscopy - Deus ex machina? World J Gastroenterol 2021; 27(32): 5351-5361 [PMID: 34539137 DOI: 10.3748/wjg.v27.i32.5351] [Reference Citation Analysis]
11 van der Zander QEW, Schreuder RM, Fonollà R, Scheeve T, van der Sommen F, Winkens B, Aepli P, Hayee B, Pischel AB, Stefanovic M, Subramaniam S, Bhandari P, de With PHN, Masclee AAM, Schoon EJ. Optical diagnosis of colorectal polyp images using a newly developed computer-aided diagnosis system (CADx) compared with intuitive optical diagnosis.Endoscopy. 2020;. [PMID: 33368056 DOI: 10.1055/a-1343-1597] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
12 Sawicki T, Ruszkowska M, Danielewicz A, Niedźwiedzka E, Arłukowicz T, Przybyłowicz KE. A Review of Colorectal Cancer in Terms of Epidemiology, Risk Factors, Development, Symptoms and Diagnosis. Cancers (Basel) 2021;13:2025. [PMID: 33922197 DOI: 10.3390/cancers13092025] [Cited by in Crossref: 3] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
13 Wang KW, Dong M. Potential applications of artificial intelligence in colorectal polyps and cancer: Recent advances and prospects. World J Gastroenterol 2020; 26(34): 5090-5100 [PMID: 32982111 DOI: 10.3748/wjg.v26.i34.5090] [Cited by in CrossRef: 7] [Cited by in F6Publishing: 8] [Article Influence: 3.5] [Reference Citation Analysis]
14 Parsa N, Byrne MF. Artificial intelligence for identification and characterization of colonic polyps. Ther Adv Gastrointest Endosc 2021;14:26317745211014698. [PMID: 34263163 DOI: 10.1177/26317745211014698] [Reference Citation Analysis]
15 Zhu Y, Wang L, Nong Y, Liang Y, Huang Z, Zhu P, Zhang Q. Serum Untargeted UHPLC-HRMS-Based Lipidomics to Discover the Potential Biomarker of Colorectal Advanced Adenoma. Cancer Manag Res 2021;13:8865-78. [PMID: 34858060 DOI: 10.2147/CMAR.S336322] [Reference Citation Analysis]
16 Choi J, Shin K, Jung J, Bae HJ, Kim DH, Byeon JS, Kim N. Convolutional Neural Network Technology in Endoscopic Imaging: Artificial Intelligence for Endoscopy. Clin Endosc. 2020;53:117-126. [PMID: 32252504 DOI: 10.5946/ce.2020.054] [Cited by in Crossref: 14] [Cited by in F6Publishing: 11] [Article Influence: 7.0] [Reference Citation Analysis]
17 Kader R, Hadjinicolaou AV, Georgiades F, Stoyanov D, Lovat LB. Optical diagnosis of colorectal polyps using convolutional neural networks. World J Gastroenterol 2021; 27(35): 5908-5918 [PMID: 34629808 DOI: 10.3748/wjg.v27.i35.5908] [Reference Citation Analysis]
18 Namikawa K, Hirasawa T, Yoshio T, Fujisaki J, Ozawa T, Ishihara S, Aoki T, Yamada A, Koike K, Suzuki H, Tada T. Utilizing artificial intelligence in endoscopy: a clinician's guide. Expert Rev Gastroenterol Hepatol. 2020;1-18. [PMID: 32500760 DOI: 10.1080/17474124.2020.1779058] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
19 Zhu XW, Yan J, He YL, Liu G, Li X. Application of deep learning based artificial intelligence technology in identification of colorectal polyps. Shijie Huaren Xiaohua Zazhi 2021; 29(20): 1201-1206 [DOI: 10.11569/wcjd.v29.i20.1201] [Reference Citation Analysis]
20 Alrumaihi F, Khan MA, Babiker AY, Alsaweed M, Azam F, Allemailem KS, Almatroudi AA, Ahamad SR, Alsuhaymi N, Alsugoor MH, Algefary AN, Khan A. The Effect of Liposomal Diallyl Disulfide and Oxaliplatin on Proliferation of Colorectal Cancer Cells: In Vitro and In Silico Analysis. Pharmaceutics 2022;14:236. [DOI: 10.3390/pharmaceutics14020236] [Reference Citation Analysis]
21 Li JW, Ang TL. Colonoscopy and artificial intelligence: Bridging the gap or a gap needing to be bridged? Artif Intell Gastrointest Endosc 2021; 2(2): 36-49 [DOI: 10.37126/aige.v2.i2.36] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
22 Joseph J, LePage EM, Cheney CP, Pawa R. Artificial intelligence in colonoscopy. World J Gastroenterol 2021; 27(29): 4802-4817 [PMID: 34447227 DOI: 10.3748/wjg.v27.i29.4802] [Reference Citation Analysis]