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Cited by in CrossRef
For: Con D, van Langenberg DR, Vasudevan A. Deep learning vs conventional learning algorithms for clinical prediction in Crohn's disease: A proof-of-concept study. World J Gastroenterol 2021; 27(38): 6476-6488 [PMID: 34720536 DOI: 10.3748/wjg.v27.i38.6476]
URL: https://www.wjgnet.com/1007-9327/full/v27/i38/6476.htm
Number Citing Articles
1
Albert E. Jergens, Romy M. Heilmann. Canine chronic enteropathy—Current state-of-the-art and emerging conceptsFrontiers in Veterinary Science 2022; 9 doi: 10.3389/fvets.2022.923013
2
Rocio Sedano, Virginia Solitano, Sudheer K. Vuyyuru, Yuhong Yuan, Jurij Hanžel, Christopher Ma, Olga Maria Nardone, Vipul Jairath. Artificial intelligence to revolutionize IBD clinical trials: a comprehensive reviewTherapeutic Advances in Gastroenterology 2025; 18 doi: 10.1177/17562848251321915
3
Laura Arosa, Miguel Camba-Gómez, Olga Golubnitschaja, Javier Conde-Aranda. Predictive, preventive and personalised approach as a conceptual and technological innovation in primary and secondary care of inflammatory bowel disease benefiting affected individuals and populationsEPMA Journal 2024; 15(1): 111 doi: 10.1007/s13167-024-00351-x
4
Paris Charilaou, Robert Battat. Machine learning models and over-fitting considerationsWorld Journal of Gastroenterology 2022; 28(5): 605-607 doi: 10.3748/wjg.v28.i5.605
5
Philippe Pinton. Impact of artificial intelligence on prognosis, shared decision-making, and precision medicine for patients with inflammatory bowel disease: a perspective and expert opinionAnnals of Medicine 2023; 55(2) doi: 10.1080/07853890.2023.2300670
6
Paolo Balasso, Cristian Taccioli, Lorenzo Serva, Luisa Magrin, Igino Andrighetto, Giorgio Marchesini. Uncovering Patterns in Dairy Cow Behaviour: A Deep Learning Approach with Tri-Axial Accelerometer DataAnimals 2023; 13(11): 1886 doi: 10.3390/ani13111886
7
Maryam Gholipour, Reza Khajouei, Parastoo Amiri, Sadrieh Hajesmaeel Gohari, Leila Ahmadian. Extracting cancer concepts from clinical notes using natural language processing: a systematic reviewBMC Bioinformatics 2023; 24(1) doi: 10.1186/s12859-023-05480-0
8
Ruining Deng, Can Cui, Lucas W. Remedios, Shunxing Bao, R. Michael Womick, Sophie Chiron, Jia Li, Joseph T. Roland, Ken S. Lau, Qi Liu, Keith T. Wilson, Yaohong Wang, Lori A. Coburn, Bennett A. Landman, Yuankai Huo. Cross-scale multi-instance learning for pathological image diagnosisMedical Image Analysis 2024; 94: 103124 doi: 10.1016/j.media.2024.103124
9
Ruining Deng, Can Cui, Lucas W. Remedios, Shunxing Bao, R. Michael Womick, Sophie Chiron, Jia Li, Joseph T. Roland, Ken S. Lau, Qi Liu, Keith T. Wilson, Yaohong Wang, Lori A. Coburn, Bennett A. Landman, Yuankai Huo. Multiscale Multimodal Medical ImagingLecture Notes in Computer Science 2022; 13594: 24 doi: 10.1007/978-3-031-18814-5_3
10
Akhil Garg, Jose Bellver, Ernesto Bosch, José Alejandro Remohí, Antonio Pellicer, Marcos Meseguer. Machine learning tool for predicting mature oocyte yield and trigger day from start of stimulation: towards personalized treatmentReproductive BioMedicine Online 2025; 50(2): 104441 doi: 10.1016/j.rbmo.2024.104441
11
Danny Con, Peter De Cruz. Defining management strategies for acute severe ulcerative colitis using predictive models: a simulation-modeling studyIntestinal Research 2024; 22(4): 439 doi: 10.5217/ir.2023.00175
12
Michael Croft, Shahram Salek-Ardakani, Carl F. Ware. Targeting the TNF and TNFR superfamilies in autoimmune disease and cancerNature Reviews Drug Discovery 2024; 23(12): 939 doi: 10.1038/s41573-024-01053-9
13
Leonardo Da Rio, Marco Spadaccini, Tommaso Lorenzo Parigi, Roberto Gabbiadini, Arianna Dal Buono, Anita Busacca, Roberta Maselli, Alessandro Fugazza, Matteo Colombo, Silvia Carrara, Gianluca Franchellucci, Ludovico Alfarone, Antonio Facciorusso, Cesare Hassan, Alessandro Repici, Alessandro Armuzzi. Artificial intelligence and inflammatory bowel disease: Where are we going?World Journal of Gastroenterology 2023; 29(3): 508-520 doi: 10.3748/wjg.v29.i3.508