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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/1948-5190/full/v26/i44/6923.htm
Number Citing Articles
1
Gerardo Alfonso Perez, Raquel Castillo. Gene Identification in Inflammatory Bowel Disease via a Machine Learning ApproachMedicina 2023; 59(7): 1218 doi: 10.3390/medicina59071218
2
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
3
Danielle Cristina Fonseca, Ilanna Marques Gomes da Rocha, Bianca Depieri Balmant, Leticia Callado, Ana Paula Aguiar Prudêncio, Juliana Tepedino Martins Alves, Raquel Susana Torrinhas, Gabriel da Rocha Fernandes, Dan Linetzky Waitzberg. Evaluation of gut microbiota predictive potential associated with phenotypic characteristics to identify multifactorial diseasesGut Microbes 2024; 16(1) doi: 10.1080/19490976.2023.2297815
4
Farkhondeh Asadi, Azamossadat Hosseini, Amir Hossein Daeechini. Designing the Essential Informational Needs of a Smartphone Application for Self‐Management of Patients With Inflammatory Bowel DiseaseHealth Science Reports 2024; 7(11) doi: 10.1002/hsr2.70186
5
Danny Con, Abhinav Vasudevan. Real-World Guidance from Artificial Intelligence? Predicting Outcomes of Inflammatory Bowel Disease Using Machine LearningDigestive Diseases and Sciences 2022; 67(10): 4604 doi: 10.1007/s10620-022-07511-x
6
H.E.C. van der Wall, R.J. Doll, G.J.P. van Westen, T. Niemeyer-van der Kolk, G. Feiss, H. Pinckaers, M.B.A. van Doorn, T. Nijsten, M.G.H. Sanders, A.F. Cohen, J. Burggraaf, R. Rissmann, L.M. Pardo. Discriminative Machine Learning Analysis for Skin Microbiome: Observing Biomarkers in Patients with Seborrheic DermatitisJournal of Artificial Intelligence for Medical Sciences 2022; 3(1-2): 1 doi: 10.55578/joaims.220819.001
7
Mahmoud Khatib A.A. Al-Ruweidi, Nada Khater, Haya Rashid Alkaabi, Maram Hasan, Mohammed Murtaza, Huseyin C. Yalcin. Immunology of the GI Tract - Recent Advances2022;  doi: 10.5772/intechopen.106185
8
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
9
Sylvie Buffet-Bataillon, Guillaume Bouguen, François Fleury, Vincent Cattoir, Yann Le Cunff. Gut microbiota analysis for prediction of clinical relapse in Crohn’s diseaseScientific Reports 2022; 12(1) doi: 10.1038/s41598-022-23757-x
10
Vangelis D. Karalis. The Integration of Artificial Intelligence into Clinical PracticeApplied Biosciences 2024; 3(1): 14 doi: 10.3390/applbiosci3010002
11
Jonathan S Galati, Robert J Duve, Matthew O'Mara, Seth A Gross. Artificial intelligence in gastroenterology: A narrative reviewArtificial Intelligence in Gastroenterology 2022; 3(5): 117-141 doi: 10.35712/aig.v3.i5.117
12
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
13
Claudia Diaconu, Monica State, Mihaela Birligea, Madalina Ifrim, Georgiana Bajdechi, Teodora Georgescu, Bogdan Mateescu, Theodor Voiosu. The Role of Artificial Intelligence in Monitoring Inflammatory Bowel Disease—The Future Is NowDiagnostics 2023; 13(4): 735 doi: 10.3390/diagnostics13040735
14
Fatemeh Moayedi, Javad Karimi, Seyed Ebrahim Dashti. CANCER PREDICTION IN INFLAMMATORY BOWEL DISEASE PATIENTS BY USING MACHINE LEARNING ALGORITHMSBiomedical Engineering: Applications, Basis and Communications 2023; 35(03) doi: 10.4015/S1016237223500114
15
Eugenia Uche-Anya, Adjoa Anyane-Yeboa, Tyler M Berzin, Marzyeh Ghassemi, Folasade P May. Artificial intelligence in gastroenterology and hepatology: how to advance clinical practice while ensuring health equityGut 2022; 71(9): 1909 doi: 10.1136/gutjnl-2021-326271
16
Giovanni Grassi, Maria Elena Laino, Massimo Claudio Fantini, Giovanni Maria Argiolas, Maria Valeria Cherchi, Refky Nicola, Clara Gerosa, Giulia Cerrone, Lorenzo Mannelli, Antonella Balestrieri, Jasjit S. Suri, Alessandro Carriero, Luca Saba. Advanced imaging and Crohn’s disease: An overview of clinical application and the added value of artificial intelligenceEuropean Journal of Radiology 2022; 157: 110551 doi: 10.1016/j.ejrad.2022.110551
17
Silvio Mazziotti, Tommaso D’Angelo, Giorgio Ascenti, Giuseppe Cicero. MR Enterography2022; : 15 doi: 10.1007/978-3-031-11930-9_3
18
Kristoffer Mazanti Cold, Anishan Vamadevan, Amihai Heen, Andreas Slot Vilmann, Morten Rasmussen, Lars Konge, Morten Bo Søndergaard Svendsen. Is the Transverse Colon Overlooked? Establishing a Comprehensive Colonoscopy Database from a Multicenter Cluster-Randomized Controlled TrialDiagnostics 2025; 15(5): 591 doi: 10.3390/diagnostics15050591
19
Weizhi Zhong, Jupeng Gong, Qiaoling Su, Mohamed A. Farag, Jesus Simal-Gandara, Hui Wang, Hui Cao. Dietary polyphenols ameliorate inflammatory bowel diseases: advances and future perspectives to maximize their nutraceutical applicationsPhytochemistry Reviews 2023;  doi: 10.1007/s11101-023-09866-z
20
Kêmily Fuentes Marques, Alana Fuentes Marques, Marina Amorim Lopes, Rodrigo Fedatto Beraldo, Talles Bazeia Lima, Ligia Yukie Sassaki. Artificial intelligence in colorectal cancer screening in patients with inflammatory bowel diseaseArtificial Intelligence in Gastrointestinal Endoscopy 2022; 3(1): 1-8 doi: 10.37126/aige.v3.i1.1
21
Chengfei Cai, Qianyun Shi, Jun Li, Yiping Jiao, Andi Xu, Yangshu Zhou, Xiangxue Wang, Chunyan Peng, Xiaoqi Zhang, Xiaobin Cui, Jun Chen, Jun Xu, Qi Sun. Pathologist-level diagnosis of ulcerative colitis inflammatory activity level using an automated histological grading methodInternational Journal of Medical Informatics 2024; 192: 105648 doi: 10.1016/j.ijmedinf.2024.105648
22
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
23
Ahmad Tamim Hamad, Parshad Suthar, Katsiaryna Laziuk, Deepthi Rao, Praveen Rao. Accurate Classification of Dysplasia in Inflammatory Bowel Disease Patients Using Deep Learning2024 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI) 2024; : 1 doi: 10.1109/BHI62660.2024.10913548
24
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 2022; 16(3): 398 doi: 10.1093/ecco-jcc/jjab155
25
Selvasankar Murugesan, Mohammed Elanbari, Dhinoth Kumar Bangarusamy, Annalisa Terranegra, Souhaila Al Khodor. Can the Salivary Microbiome Predict Cardiovascular Diseases? Lessons Learned From the Qatari PopulationFrontiers in Microbiology 2021; 12 doi: 10.3389/fmicb.2021.772736