BPG is committed to discovery and dissemination of knowledge
Cited by in CrossRef
For: Gubatan J, Levitte S, Patel A, Balabanis T, Wei MT, Sinha SR. Artificial intelligence applications in inflammatory bowel disease: Emerging technologies and future directions. World J Gastroenterol 2021; 27(17): 1920-1935 [PMID: 34007130 DOI: 10.3748/wjg.v27.i17.1920]
URL: https://www.wjgnet.com/1007-9327/full/v27/i17/1920.htm
Number Citing Articles
1
Jaehoon Jeong, Seung Taek Hong, Ihsan Ullah, Eun Sun Kim, Sang Hyun Park. Classification of the Confocal Microscopy Images of Colorectal Tumor and Inflammatory Colitis Mucosa Tissue Using Deep LearningDiagnostics 2022; 12(2): 288 doi: 10.3390/diagnostics12020288
2
Oswaldo Ortiz Zúñiga, María Gl�ria Fernández Esparrach, María Daca, María Pellisé. Artificial intelligence in gastrointestinal endoscopy: evolution to a new eraRevista Española de Enfermedades Digestivas 2022;  doi: 10.17235/reed.2022.8961/2022
3
Pedro Cardoso, Miguel Mascarenhas, João Afonso, Tiago Ribeiro, Francisco Mendes, Miguel Martins, Patrícia Andrade, Hélder Cardoso, Miguel Mascarenhas Saraiva, João P.S. Ferreira, Guilherme Macedo. Deep learning and minimally invasive inflammatory activity assessment: a proof-of-concept study for development and score correlation of a panendoscopy convolutional networkTherapeutic Advances in Gastroenterology 2024; 17 doi: 10.1177/17562848241251569
4
Stephen Spatz, Claudio L. Afonso. Non-Targeted RNA Sequencing: Towards the Development of Universal Clinical Diagnosis Methods for Human and Veterinary Infectious DiseasesVeterinary Sciences 2024; 11(6): 239 doi: 10.3390/vetsci11060239
5
Antonio Mestrovic, Nikola Perkovic, Dorotea Bozic, Marko Kumric, Marino Vilovic, Josko Bozic. Precision Medicine in Inflammatory Bowel Disease: A Spotlight on Emerging Molecular BiomarkersBiomedicines 2024; 12(7): 1520 doi: 10.3390/biomedicines12071520
6
Slawomir Wozniak, Aleksander Pawlus, Joanna Grzelak, Slawomir Chobotow, Friedrich Paulsen, Cyprian Olchowy, Urszula Zaleska-Dorobisz. Acute colonic flexures: the basis for developing an artificial intelligence-based tool for predicting the course of colonoscopyAnatomical Science International 2023; 98(1): 136 doi: 10.1007/s12565-022-00681-8
7
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
8
John Gubatan, Kian Keyashian, Samuel JS Rubin, Jenny Wang, Cyrus Buckman, Sidhartha Sinha. Anti-Integrins for the Treatment of Inflammatory Bowel Disease: Current Evidence and PerspectivesClinical and Experimental Gastroenterology 2021; : 333 doi: 10.2147/CEG.S293272
9
Andrea Padoan, Giulia Musso, Nicole Contran, Daniela Basso. Inflammation, Autoinflammation and Autoimmunity in Inflammatory Bowel DiseasesCurrent Issues in Molecular Biology 2023; 45(7): 5534 doi: 10.3390/cimb45070350
10
Shicheng Yu, Mengxian Zhang, Zhaofeng Ye, Yalong Wang, Xu Wang, Ye-Guang Chen. Development of a 32-gene signature using machine learning for accurate prediction of inflammatory bowel diseaseCell Regeneration 2023; 12(1) doi: 10.1186/s13619-022-00143-6
11
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
12
Liru Chen, Chuhan Zhang, Ruixuan Niu, Shanshan Xiong, Jinshen He, Yu Wang, Pingxin Zhang, Fengyuan Su, Zishan Liu, Longyuan Zhou, Ren Mao, Shixian Hu, Minhu Chen, Yun Qiu, Rui Feng. Multi‐Omics Biomarkers for Predicting Efficacy of Biologic and Small‐Molecule Therapies in Adults With Inflammatory Bowel Disease: A Systematic ReviewUnited European Gastroenterology Journal 2024;  doi: 10.1002/ueg2.12720
13
Johanne Brooks-Warburton, James Ashton, Anjan Dhar, Tony Tham, Patrick B Allen, Sami Hoque, Laurence B Lovat, Shaji Sebastian. Artificial intelligence and inflammatory bowel disease: practicalities and future prospectsFrontline Gastroenterology 2022; 13(4): 325 doi: 10.1136/flgastro-2021-102003
14
Hiroki Kiyokawa, Masatoshi Abe, Takahiro Matsui, Masako Kurashige, Kenji Ohshima, Shinichiro Tahara, Satoshi Nojima, Takayuki Ogino, Yuki Sekido, Tsunekazu Mizushima, Eiichi Morii. Deep Learning Analysis of Histologic Images from Intestinal Specimen Reveals Adipocyte Shrinkage and Mast Cell Infiltration to Predict Postoperative Crohn DiseaseThe American Journal of Pathology 2022; 192(6): 904 doi: 10.1016/j.ajpath.2022.03.006
15
Jia He, Shang-xian Wang, Peng Liu. Machine learning in predicting pathological complete response to neoadjuvant chemoradiotherapy in rectal cancer using MRI: a systematic review and meta-analysisBritish Journal of Radiology 2024; 97(1159): 1243 doi: 10.1093/bjr/tqae098
16
Judith A. Stibbe, Petra Hoogland, Friso B. Achterberg, Derek R. Holman, Raoul S. Sojwal, Jacobus Burggraaf, Alexander L. Vahrmeijer, Wouter B. Nagengast, Stephan Rogalla. Highlighting the Undetectable — Fluorescence Molecular Imaging in Gastrointestinal EndoscopyMolecular Imaging and Biology 2023; 25(1): 18 doi: 10.1007/s11307-022-01741-1
17
Byung Soo Yoo, Steve M D'Souza, Kevin Houston, Ankit Patel, James Lau, Alsiddig Elmahdi, Parth J Parekh, David Johnson. Artificial intelligence and colonoscopy − enhancements and improvementsArtificial Intelligence in Gastrointestinal Endoscopy 2021; 2(4): 157-167 doi: 10.37126/aige.v2.i4.157
18
João Afonso, Miguel Martins, João Ferreira, Miguel Mascarenhas. Artificial Intelligence in Capsule Endoscopy2023; : 1 doi: 10.1016/B978-0-323-99647-1.00003-4
19
Otilia Gavrilescu, Iolanda Valentina Popa, Mihaela Dranga, Ruxandra Mihai, Cristina Cijevschi Prelipcean, Cătălina Mihai. Laboratory Data and IBDQ—Effective Predictors for the Non-Invasive Machine-Learning-Based Prediction of Endoscopic Activity in Ulcerative ColitisJournal of Clinical Medicine 2023; 12(11): 3609 doi: 10.3390/jcm12113609
20
Khaled H. Mousa, Ahmed E. Nassar. Identification of hub genes and potential molecular mechanisms associated with inflammatory bowel diseases using meta-analysis of gene expression dataHighlights in BioScience 2022;  doi: 10.36462/H.BioSci.202202
21
Niel Shah, Abhilasha Jyala, Harish Patel, Jasbir Makker. Utility of artificial intelligence in colonoscopyArtificial Intelligence in Gastrointestinal Endoscopy 2021; 2(3): 78 doi: 10.37126/aige.v2.i3.78
Abstract() |  Core Tip() |  Full Article(HTML)() | Times Cited  (0) | Total Visits (0) | Open
22
David Chen, Clifton Fulmer, Ilyssa O Gordon, Sana Syed, Ryan W Stidham, Niels Vande Casteele, Yi Qin, Katherine Falloon, Benjamin L Cohen, Robert Wyllie, Florian Rieder. Application of Artificial Intelligence to Clinical Practice in Inflammatory Bowel Disease – What the Clinician Needs to KnowJournal of Crohn's and Colitis 2022; 16(3): 460 doi: 10.1093/ecco-jcc/jjab169
23
Kevin A. Chen, Nina C. Nishiyama, Meaghan M. Kennedy Ng, Alexandria Shumway, Chinmaya U. Joisa, Matthew R. Schaner, Grace Lian, Caroline Beasley, Lee-Ching Zhu, Surekha Bantumilli, Muneera R. Kapadia, Shawn M. Gomez, Terrence S. Furey, Shehzad Z. Sheikh. Linking gene expression to clinical outcomes in pediatric Crohn’s disease using machine learningScientific Reports 2024; 14(1) doi: 10.1038/s41598-024-52678-0
24
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
25
Niel Shah, Abhilasha Jyala, Harish Patel, Jasbir Makker. Utility of artificial intelligence in colonoscopyArtificial Intelligence in Gastrointestinal Endoscopy 2021; 2(3): 79-88 doi: 10.37126/aige.v2.i3.79
26
Xiaojun Li, Lamei Yan, Xuehong Wang, Chunhui Ouyang, Chunlian Wang, Jun Chao, Jie Zhang, Guanghui Lian. Predictive models for endoscopic disease activity in patients with ulcerative colitis: Practical machine learning-based modeling and interpretationFrontiers in Medicine 2022; 9 doi: 10.3389/fmed.2022.1043412
27
Gaayathri Kumarasamy, Nurul Hakimah Mohd Salim, Nur Syafiqah Mohd Afandi, Mohd Afiq Hazlami Habib, Nor Datiakma Mat Amin, Mohd Nazri Ismail, Marahaini Musa. Glycoproteomics-Based Liquid Biopsy: Translational Outlook for Colorectal Cancer Clinical Management in Southeast AsiaFuture Oncology 2023; 19(34): 2313 doi: 10.2217/fon-2023-0704
28
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
29
Nouhaila En Najih, Pr. Ahmed Moussa. New Technologies, Artificial Intelligence and Smart DataCommunications in Computer and Information Science 2024; 1728: 3 doi: 10.1007/978-3-031-47366-1_1
30
Hashim Halim-Fikri, Sharifah-Nany Rahayu-Karmilla Syed-Hassan, Wan-Khairunnisa Wan-Juhari, Mat Ghani Siti Nor Assyuhada, Yetti Hernaningsih, Narazah Mohd Yusoff, Amir Feisal Merican, Bin Alwi Zilfalil. Central resources of variant discovery and annotation and its role in precision medicineAsian Biomedicine 2022; 16(6): 285 doi: 10.2478/abm-2022-0032
31
Mohamed Abdelrahim, Katie Siggens, Yuji Iwadate, Naoto Maeda, Hein Htet, Pradeep Bhandari. New AI model for neoplasia detection and characterisation in inflammatory bowel diseaseGut 2024; 73(5): 725 doi: 10.1136/gutjnl-2023-330718
32
Jovita Relasha Lewis, Sameena Pathan, Preetham Kumar, Cifha Crecil Dias. AI in Endoscopic Gastrointestinal Diagnosis: A Systematic Review of Deep Learning and Machine Learning TechniquesIEEE Access 2024; 12: 163764 doi: 10.1109/ACCESS.2024.3483432
33
Domingo Balderramo. Role of the combination of biologics and/or small molecules in the treatment of patients with inflammatory bowel diseaseWorld Journal of Gastroenterology 2022; 28(47): 6743-6751 doi: 10.3748/wjg.v28.i47.6743
34
Sergei Bedrikovetski, Nagendra N. Dudi-Venkata, Hidde M. Kroon, Warren Seow, Ryash Vather, Gustavo Carneiro, James W. Moore, Tarik Sammour. Artificial intelligence for pre-operative lymph node staging in colorectal cancer: a systematic review and meta-analysisBMC Cancer 2021; 21(1) doi: 10.1186/s12885-021-08773-w
35
Linda S. Yang, Evelyn Perry, Leonard Shan, Helen Wilding, William Connell, Alexander J. Thompson, Andrew C. F. Taylor, Paul V. Desmond, Bronte A. Holt. Clinical application and diagnostic accuracy of artificial intelligence in colonoscopy for inflammatory bowel disease: systematic reviewEndoscopy International Open 2022; 10(07): E1004 doi: 10.1055/a-1846-0642
36
Weimin Cai, Jun Xu, Yihan Chen, Xiao Wu, Yuan Zeng, Fujun Yu. Performance of Machine Learning Algorithms for Predicting Disease Activity in Inflammatory Bowel DiseaseInflammation 2023; 46(4): 1561 doi: 10.1007/s10753-023-01827-0
37
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
38
Rohit S Vilhekar, Alka Rawekar. Artificial Intelligence in GeneticsCureus 2024;  doi: 10.7759/cureus.52035
39
Jiajie Lu, Zhiyuan Wang, Munila Maimaiti, Wenjia Hui, Adilai Abudourexiti, Feng Gao. Identification of diagnostic signatures in ulcerative colitis patients via bioinformatic analysis integrated with machine learningHuman Cell 2021; 35(1): 179 doi: 10.1007/s13577-021-00641-w
40
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
41
Sebastian Kraszewski, Witold Szczurek, Julia Szymczak, Monika Reguła, Katarzyna Neubauer. Machine Learning Prediction Model for Inflammatory Bowel Disease Based on Laboratory Markers. Working Model in a Discovery Cohort StudyJournal of Clinical Medicine 2021; 10(20): 4745 doi: 10.3390/jcm10204745
42
Antonio Meštrović, Marko Kumric, Josko Bozic. Discontinuation of therapy in inflammatory bowel disease: Current viewsWorld Journal of Clinical Cases 2024; 12(10): 1718-1727 doi: 10.12998/wjcc.v12.i10.1718
43
Elin Synnøve Røyset, Henrik P Sahlin Pettersen, Weili Xu, Anis Larbi, Arne K Sandvik, Sonja E Steigen, Ignacio Catalan‐Serra, Ingunn Bakke. Deep learning‐based image analysis reveals significant differences in the number and distribution of mucosal CD3 and γδ T cells between Crohn's disease and ulcerative colitisThe Journal of Pathology: Clinical Research 2023; 9(1): 18 doi: 10.1002/cjp2.301
44
Jinan Fiaidhi, Petros Zezos, Sabah Mohammed. Thick Data Analytics for Rating Ulcerative Colitis Severity Using Small Endoscopy Image Sample2021 IEEE International Conference on Big Data (Big Data) 2021; : 4687 doi: 10.1109/BigData52589.2021.9671327
45
Shiv Bahadur, Prashant Kumar. Deep Learning for Targeted Treatments2022; : 229 doi: 10.1002/9781119857983.ch8
46
Yun Qiu, Shixian Hu, Kang Chao, Lingjie Huang, Zicheng Huang, Ren Mao, Fengyuan Su, Chuhan Zhang, Xiaoqing Lin, Qian Cao, Xiang Gao, Minhu Chen. Developing a Machine-Learning Prediction Model for Infliximab Response in Crohn’s Disease: Integrating Clinical Characteristics and Longitudinal Laboratory TrendsInflammatory Bowel Diseases 2024;  doi: 10.1093/ibd/izae176
47
Abeer Aljohani, Nawaf Alharbe, Rabia Emhamed Al Mamlook, Mashael M. Khayyat. A hybrid combination of CNN Attention with optimized random forest with grey wolf optimizer to discriminate between Arabic hateful, abusive tweetsJournal of King Saud University - Computer and Information Sciences 2024; 36(2): 101961 doi: 10.1016/j.jksuci.2024.101961
48
Yi Fei Chen, Liu Liu, Bin Lyu, Ye Yang, Si Si Zheng, Xuan Huang, Yi Xu, Yi Hong Fan. Role of artificial intelligence in Crohn's disease intestinal strictures and fibrosisJournal of Digestive Diseases 2024; 25(8): 476 doi: 10.1111/1751-2980.13308
49
Claudio L. Afonso, Anna M. Afonso. Next-Generation Sequencing for the Detection of Microbial Agents in Avian Clinical SamplesVeterinary Sciences 2023; 10(12): 690 doi: 10.3390/vetsci10120690
50
Lin Zhang, Rui Mao, Chung Tai Lau, Wai Chak Chung, Jacky C. P. Chan, Feng Liang, Chenchen Zhao, Xuan Zhang, Zhaoxiang Bian. Identification of useful genes from multiple microarrays for ulcerative colitis diagnosis based on machine learning methodsScientific Reports 2022; 12(1) doi: 10.1038/s41598-022-14048-6
51
Chen Sun, Xiangshu Cheng, Jing Xu, Haiyan Chen, Junxian Tao, Yu Dong, Siyu Wei, Rui Chen, Xin Meng, Yingnan Ma, Hongsheng Tian, Xuying Guo, Shuo Bi, Chen Zhang, Jingxuan Kang, Mingming Zhang, Hongchao Lv, Zhenwei Shang, Wenhua Lv, Ruijie Zhang, Yongshuai Jiang. A review of disease risk prediction methods and applications in the omics eraPROTEOMICS 2024; 24(18) doi: 10.1002/pmic.202300359
52
David T. Rubin, Klaus Gottlieb, Jean-Frederic Colombel, Jean-Pierre Schott, Lavi Erisson, Bill Prucka, Sloane Allebes Phillips, John Kwon, Jonathan Ng, James McGill. Development of a Novel Ulcerative Colitis Endoscopic Mayo Score Prediction Model Using Machine LearningGastro Hep Advances 2023; 2(7): 935 doi: 10.1016/j.gastha.2023.06.003
53
Mohammed Al-Biltagi, Nermin Kamal Saeed, Samara Qaraghuli. Gastrointestinal disorders in children with autism: Could artificial intelligence help?Artificial Intelligence in Gastroenterology 2022; 3(1): 1-12 doi: 10.35712/aig.v3.i1.1
54
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
55
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
56
Maurizio Cè, Natascha Claudia D'Amico, Giulia Maria Danesini, Chiara Foschini, Giancarlo Oliva, Carlo Martinenghi, Michaela Cellina. Ultrasound Elastography: Basic Principles and Examples of Clinical Applications with Artificial Intelligence—A ReviewBioMedInformatics 2023; 3(1): 17 doi: 10.3390/biomedinformatics3010002
57
Ami Kawamoto, Kento Takenaka, Ryuichi Okamoto, Mamoru Watanabe, Kazuo Ohtsuka. Systematic review of artificial intelligence‐based image diagnosis for inflammatory bowel diseaseDigestive Endoscopy 2022; 34(7): 1311 doi: 10.1111/den.14334
58
Maheeba Abdulla, Nafeesa Mohammed. A Review on Inflammatory Bowel Diseases: Recent Molecular Pathophysiology AdvancesBiologics: Targets and Therapy 2022; : 129 doi: 10.2147/BTT.S380027
59
Asif Hassan Syed, Hamza Ali S. Abujabal, Shakeel Ahmad, Sharaf J. Malebary, Nashwan Alromema. Advances in Inflammatory Bowel Disease Diagnostics: Machine Learning and Genomic Profiling Reveal Key Biomarkers for Early DetectionDiagnostics 2024; 14(11): 1182 doi: 10.3390/diagnostics14111182
60
Tanya Sinha, Zukhruf Zain, Syed Faqeer Hussain Bokhari, Sarosh Waheed, Taufiqa Reza, Anthony Eze-Odurukwe, Mitwa Patel, Mohammed Khaleel I KH Almadhoun , Azlaan Hussain, Ibrahim Reyaz. Navigating the Gut-Cardiac Axis: Understanding Cardiovascular Complications in Inflammatory Bowel DiseaseCureus 2024;  doi: 10.7759/cureus.55268
61
Mirja Mittermaier, Marium M. Raza, Joseph C. Kvedar. Bias in AI-based models for medical applications: challenges and mitigation strategiesnpj Digital Medicine 2023; 6(1) doi: 10.1038/s41746-023-00858-z
62
Gerardo Alfonso Perez, Raquel Castillo. Gene Identification in Inflammatory Bowel Disease via a Machine Learning ApproachMedicina 2023; 59(7): 1218 doi: 10.3390/medicina59071218
63
Zixi Jia, Yilu Wang, Shengming Li, Meiqi Yang, Zhongyuan Liu, Huijing Zhang. MICDnet: Multimodal information processing networks for Crohn’s disease diagnosisComputers in Biology and Medicine 2024; 168: 107790 doi: 10.1016/j.compbiomed.2023.107790
64
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
65
Harris A Ahmad, James E East, Remo Panaccione, Simon Travis, James B Canavan, Keith Usiskin, Michael F Byrne. Artificial Intelligence in Inflammatory Bowel Disease Endoscopy: Implications for Clinical TrialsJournal of Crohn's and Colitis 2023; 17(8): 1342 doi: 10.1093/ecco-jcc/jjad029
66
Laetitia Ricci, Yannick Toussaint, Justine Becker, Hiba Najjar, Alix Renier, Myriam Choukour, Anne Buisson, Corinne Devos, Jonathan Epstein, Laurent Peyrin Biroulet, Francis Guillemin. Web-based and machine learning approaches for identification of patient-reported outcomes in inflammatory bowel diseaseDigestive and Liver Disease 2022; 54(4): 483 doi: 10.1016/j.dld.2021.09.005
67
Zahra Sadat Manzari, Mohammad Sajjad Ghaderi, Hassan Vossoughinia, Hossein Rafiei, Mohamad Hossein Mafi. Comparison of the effect of self-care education with two methods, teach-back and smartphone application, on the adherence to treatment in patients with inflammatory bowel diseaseSaudi Journal of Gastroenterology 2024; 30(6): 407 doi: 10.4103/sjg.sjg_200_24
68
Fernando Gomollón, Javier P. Gisbert, Iván Guerra, Rocío Plaza, Ramón Pajares Villarroya, Luis Moreno Almazán, Mª Carmen López Martín, Mercedes Domínguez Antonaya, María Isabel Vera Mendoza, Jesús Aparicio, Vicente Martínez, Ignacio Tagarro, Alonso Fernández-Nistal, Sara Lumbreras, Claudia Maté, Carmen Montoto. Clinical characteristics and prognostic factors for Crohn’s disease relapses using natural language processing and machine learning: a pilot studyEuropean Journal of Gastroenterology & Hepatology 2022; 34(4): 389 doi: 10.1097/MEG.0000000000002317
69
Sang-Bum Kang, Hyeonwoo Kim, Sangsoo Kim, Jiwon Kim, Soo-Kyung Park, Chil-Woo Lee, Kyeong Ok Kim, Geom-Seog Seo, Min Suk Kim, Jae Myung Cha, Ja Seol Koo, Dong-Il Park. Potential Oral Microbial Markers for Differential Diagnosis of Crohn’s Disease and Ulcerative Colitis Using Machine Learning ModelsMicroorganisms 2023; 11(7): 1665 doi: 10.3390/microorganisms11071665
70
Lusine Khachatryan, Yang Xiang, Artem Ivanov, Enrico Glaab, Garrett Graham, Ilaria Granata, Maurizio Giordano, Lucia Maddalena, Marina Piccirillo, Ichcha Manipur, Giacomo Baruzzo, Marco Cappellato, Batiste Avot, Adrian Stan, James Battey, Giuseppe Lo Sasso, Stephanie Boue, Nikolai V. Ivanov, Manuel C. Peitsch, Julia Hoeng, Laurent Falquet, Barbara Di Camillo, Mario R. Guarracino, Vladimir Ulyantsev, Nicolas Sierro, Carine Poussin. Results and lessons learned from the sbv IMPROVER metagenomics diagnostics for inflammatory bowel disease challengeScientific Reports 2023; 13(1) doi: 10.1038/s41598-023-33050-0
71
Muhammad Ali Muzammil, FNU Fariha, Tirath Patel, Rohab Sohail, Munesh Kumar, Ejaz Khan, Bushra Khanam, Satesh Kumar, Mahima Khatri, Giustino Varrassi, Prasanthi Vanga. Advancements in Inflammatory Bowel Disease: A Narrative Review of Diagnostics, Management, Epidemiology, Prevalence, Patient Outcomes, Quality of Life, and Clinical PresentationCureus 2023;  doi: 10.7759/cureus.41120