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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/1948-5190/full/v27/i38/6476.htm
Number Citing Articles
1
Julien Kirchgesner, Bram Verstockt, Michel Adamina, Kristine H Allin, Mariangela Allocca, Arno R Bourgonje, Johan Burisch, Glen Doherty, Parambir S Dulai, Alaa El-Hussuna, Ravi Misra, Nurulamin Noor, Valérie Pittet, Nick Powell, Iago Rodríguez-Lago, Sophie Restellini. ECCO Topical Review on Predictive Models on Inflammatory Bowel Disease Disease Course and Treatment ResponseJournal of Crohn's and Colitis 2025; 19(6) doi: 10.1093/ecco-jcc/jjaf073
2
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
3
Yiting Wang, Jialin Song, Zhuoling Zheng, Xiang Peng, Xiaoyan Li, Wenjiao Wu. Development and Validation of a Machine Learning Model to Predict Anti-Drug Antibody Formation During Infliximab Induction in Crohn’s DiseaseBiomedicines 2025; 13(10): 2464 doi: 10.3390/biomedicines13102464
4
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
5
Shu-Qi Ren, Jin-Man Chen, Chuang Cai. Translational artificial intelligence in gastrointestinal and hepatic disorders: Advancing intelligent clinical decision-making for diagnosis, treatment, and prognosisWorld Journal of Gastroenterology 2025; 31(36): 110742 doi: 10.3748/wjg.v31.i36.110742
6
Minjung Kim, Joo Hye Song, Sung Noh Hong, Myeong Gyu Kim, Eun Ran Kim, Dong Kyung Chang, Young-Ho Kim. Prediction of infliximab and anti-drug antibody concentrations in patients with inflammatory bowel disease using machine learning models with real-world data from a prospective cohort studyFrontiers in Pharmacology 2026; 17 doi: 10.3389/fphar.2026.1731193
7
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
8
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
9
Horia Minea, Ana-Maria Singeap, Manuela Minea, Stefan Chiriac, Carol Stanciu, Anca Trifan. Artificial intelligence in inflammatory bowel disease: Current applications and future directionsWorld Journal of Gastroenterology 2025; 31(39): 111353 doi: 10.3748/wjg.v31.i39.111353
10
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
11
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
12
Diletta De Deo, Arianna Dal Buono, Roberto Gabbiadini, Olga Maria Nardone, Rocio Ferreiro-Iglesias, Giuseppe Privitera, Cristiana Bonifacio, Manuel Barreiro-de Acosta, Cristina Bezzio, Alessandro Armuzzi. Digital biomarkers and artificial intelligence: a new frontier in personalized management of inflammatory bowel diseaseFrontiers in Immunology 2025; 16 doi: 10.3389/fimmu.2025.1637159
13
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
14
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
15
Sandeep Mukherji, Saurabh Singh Tomar, Sharad Nigam, Sachin Kumar Sonker, Shesh Kumar. Soft Computing: Theories and ApplicationsLecture Notes in Networks and Systems 2025; 1343: 95 doi: 10.1007/978-981-96-5955-5_9
16
Johan Burisch, Rupa Banerjee, Gillian Watermeyer. Equitable access to inflammatory bowel disease care: challenges, strategies, and future directionsJournal of Crohn’s and Colitis 2026; 20(Supplement_2): ii11 doi: 10.1093/ecco-jcc/jjaf205
17
Mukhtar Ijaiya, Erica Troncoso, Marang Mutloatse, Duruanyanwu Ifeanyi, Benjamin Obasa, Franklin Emerenini, Lucien De Voux, Thobeka Mnguni, Shantelle Parrott, Ejike Okwor, Babafemi Dare, Oluwayemisi Ogundare, Emmanuel Atuma, Molly Strachan, Ruby Fayorsey, Kelly Curran, Somayeh Hessam. Use of machine learning in predicting continuity of HIV treatment in selected Nigerian StatesPLOS Global Public Health 2025; 5(4): e0004497 doi: 10.1371/journal.pgph.0004497
18
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
19
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
20
Sabrina Meng, Hersh Sagreiya, Negar Orangi-Fard. Prediction of Chronic Obstructive Pulmonary Disease Using Machine Learning, Clinical Summary Notes, and Vital Signs: A Single-Center Retrospective Cohort Study in the United StatesAdvances in Respiratory Medicine 2026; 94(1): 5 doi: 10.3390/arm94010005
21
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
22
Lijuan Sun, Xiaomei Sun, Cuixia Qiao, Yongpan Lu, Qian Li, Qianqian Wang, Hairui Gao. Precision medicine in Crohn’s disease: Navigating the path from biomarker discovery to clinical implementationSaudi Journal of Gastroenterology 2026;  doi: 10.4103/sjg.sjg_384_25
23
Nunzia Labarile, Alessandro Vitello, Emanuele Sinagra, Olga Maria Nardone, Giulio Calabrese, Federico Bonomo, Marcello Maida, Marietta Iacucci. Artificial Intelligence in Advancing Inflammatory Bowel Disease Management: Setting New StandardsCancers 2025; 17(14): 2337 doi: 10.3390/cancers17142337
24
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
25
Li Ma, Yuepeng Chen, Xiangling Fu, Jing Qin, Yanwen Luo, Yuanjing Gao, Wenbo Li, Mengsu Xiao, Zheng Cao, Jialin Shi, Qingli Zhu, Chenyi Guo, Ji Wu. Predicting mucosal healing in Crohn’s disease: development of a deep-learning model based on intestinal ultrasound imagesInsights into Imaging 2025; 16(1) doi: 10.1186/s13244-025-02014-5
26
Reza Maddah, Zahra Sadat Aghili, Fahimeh Ghanbari, Amirhossein Hajialiasgary Najafabadi, Sedigheh Asgary. Integrative bioinformatics and deep learning to identify common genetic pathways in Crohn’s disease and ischemic cardiomyopathyJournal of Genetic Engineering and Biotechnology 2025; 23(3): 100529 doi: 10.1016/j.jgeb.2025.100529
27
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