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Cited by in CrossRef
For: Kohli A, Holzwanger EA, Levy AN. Emerging use of artificial intelligence in inflammatory bowel disease. World J Gastroenterol 2020; 26(44): 6923-6928 [PMID: 33311940 DOI: 10.3748/wjg.v26.i44.6923]
URL: https://www.wjgnet.com/1007-9327/full/v26/i44/6923.htm
Number Citing Articles
1
Kamila Majidova, Julia Handfield, Kamran Kafi, Ryan D. Martin, Ryszard Kubinski. Role of Digital Health and Artificial Intelligence in Inflammatory Bowel Disease: A Scoping ReviewGenes 2021; 12(10): 1465 doi: 10.3390/genes12101465
2
Claudio Fiorillo, Carlo Alberto Schena, Giuseppe Quero, Vito Laterza, Daniela Pugliese, Giuseppe Privitera, Fausto Rosa, Tommaso Schepis, Lisa Salvatore, Brunella Di Stefano, Luigi Larosa, Laura Maria Minordi, Luigi Natale, Giampaolo Tortora, Alessandro Armuzzi, Sergio Alfieri. Challenges in Crohn’s Disease Management after Gastrointestinal Cancer DiagnosisCancers 2021; 13(3): 574 doi: 10.3390/cancers13030574
3
Biljana Stankovic, Nikola Kotur, Gordana Nikcevic, Vladimir Gasic, Branka Zukic, Sonja Pavlovic. Machine Learning Modeling from Omics Data as Prospective Tool for Improvement of Inflammatory Bowel Disease Diagnosis and Clinical ClassificationsGenes 2021; 12(9): 1438 doi: 10.3390/genes12091438
4
Nghia H Nguyen, Dominic Picetti, Parambir S Dulai, Vipul Jairath, William J Sandborn, Lucila Ohno-Machado, Peter L Chen, Siddharth Singh. Machine Learning-based Prediction Models for Diagnosis and Prognosis in Inflammatory Bowel Diseases: A Systematic ReviewJournal of Crohn's and Colitis 2021;  doi: 10.1093/ecco-jcc/jjab155
5
Danny Con, Daniel R van Langenberg, Abhinav Vasudevan. Deep learning <i>vs</i> conventional learning algorithms for clinical prediction in Crohn's disease: A proof-of-concept studyWorld Journal of Gastroenterology 2021; 27(38): 6476-6488 doi: 10.3748/wjg.v27.i38.6476