Intestinal Research

Simon Travis

6 Articles

IBD

Artificial intelligence in inflammatory bowel disease: implications for clinical practice and future directions: Harris A. Ahmad, James E. East, Remo Panaccione, Simon Travis, James B. Canavan, Keith Usiskin, Michael F. Byrne; Intest Res 2023;21(3):283-294. Published online April 20, 2023; DOI: https://doi.org/10.5217/ir.2023.00020

Inflammatory bowel disease encompasses Crohn’s disease and ulcerative colitis and is characterized by uncontrolled, relapsing, and remitting course of inflammation in the gastrointestinal tract. Artificial intelligence represents a new era within the field of gastroenterology, and the amount of research surrounding artificial intelligence in patients with inflammatory bowel disease is on the rise. As clinical trial outcomes and treatment targets evolve in inflammatory bowel disease, artificial intelligence may prove as a valuable tool for providing accurate, consistent, and reproducible evaluations of endoscopic appearance and histologic activity, thereby optimizing the diagnosis process and identifying disease severity. Furthermore, as the applications of artificial intelligence for inflammatory bowel disease continue to expand, they may present an ideal opportunity for improving disease management by predicting treatment response to biologic therapies and for refining the standard of care by setting the basis for future treatment personalization and cost reduction. The purpose of this review is to provide an overview of the unmet needs in the management of inflammatory bowel disease in clinical practice and how artificial intelligence tools can address these gaps to transform patient care.

Citations

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Deep Learning Model Using Stool Pictures for Predicting Endoscopic Mucosal Inflammation in Patients With Ulcerative Colitis
Jung Won Lee, Dongwon Woo, Kyeong Ok Kim, Eun Soo Kim, Sung Kook Kim, Hyun Seok Lee, Ben Kang, Yoo Jin Lee, Jeongseok Kim, Byung Ik Jang, Eun Young Kim, Hyeong Ho Jo, Yun Jin Chung, Hanjun Ryu, Soo-Kyung Park, Dong-Il Park, Hosang Yu, Sungmoon Jeong
American Journal of Gastroenterology.2025; 120(1): 213. CrossRef
The Role of Artificial Intelligence and Big Data for Gastrointestinal Disease
Nicholas Mathew Holt, Michael Francis Byrne
Gastrointestinal Endoscopy Clinics of North America.2025; 35(2): 291. CrossRef
Ulcerative Colitis Severity Classification and Localized Extent (UC-SCALE): An Artificial Intelligence Scoring System for a Spatial Assessment of Disease Severity in Ulcerative Colitis
Benjamin Gutierrez-Becker, Stefan Fraessle, Heming Yao, Jerome Luscher, Rafal Girycki, Bartosz Machura, Janusz Czornik, Jaroslaw Goslinsky, Marek Pitura, Steven Levitte, Josep Arús-Pous, Emily Fisher, Daniela Bojic, David Richmond, Amelie E Bigorgne, Marc
Journal of Crohn's and Colitis.2025;[Epub] CrossRef
Artificial intelligence–enabled histology exhibits comparable accuracy to pathologists in assessing histological remission in ulcerative colitis: a systematic review, meta-analysis, and meta-regression
Miguel Puga-Tejada, Snehali Majumder, Yasuharu Maeda, Irene Zammarchi, Ilaria Ditonno, Giovanni Santacroce, Ivan Capobianco, Carlos Robles-Medranda, Subrata Ghosh, Marietta Iacucci
Journal of Crohn's and Colitis.2025;[Epub] CrossRef
Artificial intelligence to revolutionize IBD clinical trials: a comprehensive review
Rocio Sedano, Virginia Solitano, Sudheer K. Vuyyuru, Yuhong Yuan, Jurij Hanžel, Christopher Ma, Olga Maria Nardone, Vipul Jairath
Therapeutic Advances in Gastroenterology.2025;[Epub] CrossRef
The global research of artificial intelligence on inflammatory bowel disease: A bibliometric analysis
Suqi Zeng, Chenyu Dong, Chuan Liu, Junhai Zhen, Yu Pu, Jiaming Hu, Weiguo Dong
DIGITAL HEALTH.2025;[Epub] CrossRef
Rediscovering histology – the application of artificial intelligence in inflammatory bowel disease histologic assessment
Giovanni Santacroce, Irene Zammarchi, Olga Maria Nardone, Ivan Capobianco, Miguel Puga-Tejada, Snehali Majumder, Subrata Ghosh, Marietta Iacucci
Therapeutic Advances in Gastroenterology.2025;[Epub] CrossRef
Possibilities of using artificial intelligence technologies in the morphological diagnosis of inflammatory bowel diseases (literature review)
E. G. Churilova, A. B. Kazumova, Kh. M. Akhrieva, N. V. Pachuasvili, A. S. Tertychnyy
Bulletin of the Medical Institute "REAVIZ" (REHABILITATION, DOCTOR AND HEALTH).2025; 15(1): 22. CrossRef
Mining Transcriptional Data for Precision Medicine: Bioinformatics Insights into Inflammatory Bowel Disease
Arman Shahriari, Shokoofeh Amirzadeh Shams, Hamidreza Mahboobi, Maryam Yazdanparast, Amirreza Jabbaripour Sarmadian
Current Bioinformatics.2025; 20(4): 289. CrossRef
Synergies Among Clinicians, Academia, and Industry in the Age of Artificial Intelligence
Michael F. Byrne, Jens Rittscher, James E. East
Gastroenterology.2025;[Epub] CrossRef
Diagnostic Methods and Biomarkers in Inflammatory Bowel Disease
Andrew M. Kaz, Nanda Venu
Diagnostics.2025; 15(11): 1303. CrossRef
The Histological Detection of Ulcerative Colitis Using a No-Code Artificial Intelligence Model
Yuichiro Hamamoto, Michihiro Kawamura, Hiroki Uchida, Kazuhiro Hiramatsu, Chiaki Katori, Hinako Asai, Shigeki Shimizu, Satoshi Egawa, Kyotaro Yoshida
International Journal of Surgical Pathology.2024; 32(5): 890. CrossRef
Could histologic healing be a new treatment target in patients with ulcerative colitis?
Soyoung Kim, Sang Hyoung Park
The Korean Journal of Internal Medicine.2024; 39(1): 2. CrossRef
Machine learning in the assessment and management of acute gastrointestinal bleeding
Gaurav Bhaskar Nigam, Michael F Murphy, Simon P L Travis, Adrian J Stanley
BMJ Medicine.2024; 3(1): e000699. CrossRef
The Role of Artificial Intelligence in the Diagnosis and Treatment of Ulcerative Colitis
Petar Uchikov, Usman Khalid, Nikola Vankov, Maria Kraeva, Krasimir Kraev, Bozhidar Hristov, Milena Sandeva, Snezhanka Dragusheva, Dzhevdet Chakarov, Petko Petrov, Bistra Dobreva-Yatseva, Ivan Novakov
Diagnostics.2024; 14(10): 1004. CrossRef
Artificial intelligence and endo-histo-omics: new dimensions of precision endoscopy and histology in inflammatory bowel disease
Marietta Iacucci, Giovanni Santacroce, Irene Zammarchi, Yasuharu Maeda, Rocío Del Amor, Pablo Meseguer, Bisi Bode Kolawole, Ujwala Chaudhari, Antonio Di Sabatino, Silvio Danese, Yuichi Mori, Enrico Grisan, Valery Naranjo, Subrata Ghosh
The Lancet Gastroenterology & Hepatology.2024; 9(8): 758. CrossRef
Summary of the best evidence on self-management support schemes for patients with inflammatory bowel disease based on mobile health systems
Chenfei Ren, Yunxian Zhou, Qian Cai, Mi Zhou
DIGITAL HEALTH.2024;[Epub] CrossRef
Deep Learning-Based Real-Time Organ Localization and Transit Time Estimation in Wireless Capsule Endoscopy
Seung-Joo Nam, Gwiseong Moon, Jung-Hwan Park, Yoon Kim, Yun Jeong Lim, Hyun-Soo Choi
Biomedicines.2024; 12(8): 1704. CrossRef
Dye-based chromoendoscopy detects more neoplasia than white light endoscopy in patients with primary sclerosing cholangitis and IBD
Rodrigo V Motta, Vipin Gupta, Karen Hartery, Paul Bassett, Simon J Leedham, Roger W Chapman, Simon PL Travis, Emma L Culver, James E. East
Endoscopy International Open.2024; 12(11): E1285. CrossRef
Potential Oral Microbial Markers for Differential Diagnosis of Crohn’s Disease and Ulcerative Colitis Using Machine Learning Models
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
Microorganisms.2023; 11(7): 1665. CrossRef

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Miscellaneous

JAK inhibitor, a new player for treatment-refractory microscopic colitis: Anne Druez, Simon Travis, Jean-François Rahier; Intest Res 2023;21(3):411-412. Published online July 4, 2023; DOI: https://doi.org/10.5217/ir.2023.00030

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Endoscopic findings of immune checkpoint inhibitor-related gastrointestinal adverse events
Min Kyu Kim, Sung Wook Hwang
Clinical Endoscopy.2024; 57(6): 725. CrossRef

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116 Download
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Inflammatory bowel diseases

Real-time data monitoring for ulcerative colitis: patient perception and qualitative analysis: Alissa Walsh, Lawrence Matini, Christopher Hinds, Vanashree Sexton, Oliver Brain, Satish Keshav, John Geddes, Guy Goodwin, Gary Collins, Simon Travis, Michele Peters; Intest Res 2019;17(3):365-374. Published online May 31, 2019; DOI: https://doi.org/10.5217/ir.2018.00173

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Background/Aims
TrueColours ulcerative colitis (TCUC) is a comprehensive web-based program that functions through email, providing direct links to questionnaires. Several similar programs are available, however patient perspectives are unexplored.
Methods
A pilot study was conducted to determine feasibility, usability and patient perceptions of real-time data collection (daily symptoms, fortnightly quality of life, 3 monthly outcomes). TCUC was adapted from a web-based program for patients with relapsing-remitting bipolar disorder, using validated UC indices. A semi-structured interview was developed and audio-recorded face-to-face interviews were conducted after 6 months of interaction with TCUC. Transcripts were coded in NVivo11, a qualitative data analysis software package. An inductive approach and thematic analysis was conducted.
Results
TCUC was piloted in 66 patients for 6 months. Qualitative analysis currently defies statistical appraisal beyond “data saturation,” even if it has more influence on clinical practice than quantitative data. A total of 28 face-to-face interviews were conducted. Six core themes emerged: awareness, control, decision-making, reassurance, communication and burden of treatment. There was a transcending overarching theme of patient empowerment, which cut across all aspects of the TCUC experience.
Conclusions
Patient perception of the impact of real-time data collection was extremely positive. Patients felt empowered as a product of the self-monitoring format of TCUC, which may be a way of improving self-management of UC whilst also decreasing the burden on the individual and healthcare services.

Citations

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Investigating Patient Perspectives on Using eHealth Technologies for the Self-Management of Inflammatory Bowel Disease: Mixed Methods Study
Sander Hermsen, Danielle Tump, Eva Wentink, Marjolijn Duijvestein
Journal of Medical Internet Research.2024; 26: e53512. CrossRef
The body as an obstacle and the “other”. How patients with chronic inflammatory bowel diseases view their body, self and the good life
Anke Erdmann, Christoph Rehmann-Sutter, Florian Schrinner, Claudia Bozzaro
BMC Medical Ethics.2024;[Epub] CrossRef
Development of the Escalation of Therapy or Intervention (ETI) Calculator for Patients with Ulcerative Colitis Using ePROMs
Lawrence Matini, Thomas P Chapman, Ramona Kantschuster, Jean Wilson, Adib Tarafdar, Moheez Hussain, Kaiyang Song, Daniel M Simadibrata, Pavetha Seeva, Lydia White, Jessica Slater, Andrey Kormilitzin, Gary Collins, Simon P L Travis, Alissa Walsh
Journal of Crohn's and Colitis.2023; 17(11): 1744. CrossRef
Deep learning model for distinguishing Mayo endoscopic subscore 0 and 1 in patients with ulcerative colitis
Ji Eun Kim, Yoon Ho Choi, Yeong Chan Lee, Gyeol Seong, Joo Hye Song, Tae Jun Kim, Eun Ran Kim, Sung Noh Hong, Dong Kyung Chang, Young-Ho Kim, Soo-Yong Shin
Scientific Reports.2023;[Epub] CrossRef
Patient-reported Outcomes: the ICHOM Standard Set for Inflammatory Bowel Disease in Real-life Practice Helps Quantify Deficits in Current Care
Darren Wong, Lawrence Matini, Andrey Kormilitzin, Ramona Kantschuster, Daniel Martin Simadibrata, Sara Lyden, Jean Wilson, Oliver A Brain, Rebecca Palmer, Tim Ambrose, Jack Satsangi, Matthew South, John Geddes, Keith Bodger, Simon P L Travis, Alissa Walsh
Journal of Crohn's and Colitis.2022; 16(12): 1874. CrossRef
Analysis of the Current Situation of Teaching and Learning of Ideological and Political Theory Courses by Deep Learning
Jin Chao, Yijiang Zhang, Arpit Bhardwaj
Computational Intelligence and Neuroscience.2022; 2022: 1. CrossRef
Ulcerative Colitis Narrative Global Survey Findings: Communication Gaps and Agreements Between Patients and Physicians
David T Rubin, Ailsa Hart, Remo Panaccione, Alessandro Armuzzi, Ulla Suvanto, J Jasper Deuring, John Woolcott, Joseph C Cappelleri, Kathy Steinberg, Laura Wingate, Stefan Schreiber
Inflammatory Bowel Diseases.2021; 27(7): 1096. CrossRef
Telehealth and mobile health interventions in adults with inflammatory bowel disease: A mixed‐methods systematic review
Suja P. Davis, Megan Suzanne Hardin Ross, Reuben Adatorwovor, Holly Wei
Research in Nursing & Health.2021; 44(1): 155. CrossRef
COVID-19 and Gastrointestinal Disease: Implications for the Gastroenterologist
Richard H. Hunt, James E. East, Angel Lanas, Peter Malfertheiner, Jack Satsangi, Carmelo Scarpignato, Gwilym J. Webb
Digestive Diseases.2021; 39(2): 119. CrossRef
The True Colours Remote Symptom Monitoring System: A Decade of Evolution
Sarah M Goodday, Lauren Atkinson, Guy Goodwin, Kate Saunders, Matthew South, Clare Mackay, Mike Denis, Chris Hinds, Mary-Jane Attenburrow, Jim Davies, James Welch, William Stevens, Karen Mansfield, Juulia Suvilehto, John Geddes
Journal of Medical Internet Research.2020; 22(1): e15188. CrossRef
Developments and challenges of e-health strategies for people with inflammatory bowel disease
Pearl Avery
British Journal of Healthcare Management.2020; 26(3): 73. CrossRef
Pathogenesis and clinical perspectives of extraintestinal manifestations in inflammatory bowel diseases
Jung Min Kim, Jae Hee Cheon
Intestinal Research.2020; 18(3): 249. CrossRef
The UK IBD Registry COVID-19 Risk Tool; Patient Generated Data Can Improve the Hospital Record
Nicholas A. Kennedy, Naila Arebi, Keith Bodger, Vida Cairnes, R. Fraser Cummings, Liz Dobson, Stephen Grainger, Paul Harrow, A. Barney Hawthorne, Gareth-Rhys Jones, Alexandra Kent, Shaji Sebastian, Christian Selinger, Gareth J. Walker, Lisa Younge, Stuart
SSRN Electronic Journal .2020;[Epub] CrossRef

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IBD

Improving the quality of care for inflammatory bowel disease: Byong Duk Ye, Simon Travis; Intest Res 2019;17(1):45-53. Published online November 20, 2018; DOI: https://doi.org/10.5217/ir.2018.00113

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Great strides have been achieved in the development of quality-of-care measures and standards for inflammatory bowel disease (IBD) over the last decade. The central structural component of care in IBD revolves around the multidisciplinary team, which should be equipped with the necessary resources to operate and implement decisions. Process measures have been defined by interest groups and can be adapted into process tools for the delivery of care for various patient subgroups and clinical scenarios. The emerging treat-to-target approach to IBD management may be used to achieve optimal long-term and holistic patient-centred outcomes, such as survival, control of inflammation and disease progression, symptomatic remission, quality of life and complications. Other important quality-of-care outcome measures for IBD include disutility of care, healthcare utilization and other patient-reported outcomes such as nutritional status and impact of fistulae. The current challenge for healthcare providers and health systems is the integration of quality-of-care structures and processes into clinical practice, and the consistent delivery of updated evidence-based quality IBD care to various patient populations by individual health care providers. Finally, the awareness and appreciation for quality of care in IBD is increasing in Asia, and Asian healthcare institutions should be encouraged to take the lead in improving the quality of care in IBD.

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IBD

What's app? Electronic health technology in inflammatory bowel disease: Alissa Walsh, Simon Travis; Intest Res 2018;16(3):366-373. Published online July 27, 2018; DOI: https://doi.org/10.5217/ir.2018.16.3.366

Abstract PDF PubReader ePub

Electronic health (eHealth) data collection is increasingly used in many chronic illnesses, to track pattern of disease. eHealth systems have the potential to revolutionize care. Inflammatory bowel disease (IBD) is a paradigm for such an approach: this is a chronic disease that usually affects young and technologically literate patient population, who are motivated to be involved in their own care. A range of eHealth technologies are available for IBD. This review considers the strengths and weaknesses of 7 platforms that focus on patient-provider interaction. These have been developed in Denmark, United States, the Netherlands, and the United Kingdom, demonstrating an international interest in this form of technology and interaction. Not only do these technologies aim to improve care but they also have the potential to collect large amounts of information. Information includes demographics and patient reported outcomes (symptoms, quality of life), quality of care (steroid use, among other metrics) and outcomes such as hospitalization. These data could inform quality improvement programmes to improve their focus. eHealth technology is also open to machine learning to analyze large data sets, through which personalized algorithms may be developed.

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Adalimumab induction and maintenance therapy achieve clinical remission and response in Chinese patients with Crohn's disease: Kai-Chun Wu, Zhi Hua Ran, Xiang Gao, Minhu Chen, Jie Zhong, Jian-Qiu Sheng, Michael A Kamm, Simon Travis, Kori Wallace, Nael M Mostafa, Marisa Shapiro, Yao Li, Roopal B Thakkar, Anne M Robinson; Intest Res 2016;14(2):152-163. Published online April 27, 2016; DOI: https://doi.org/10.5217/ir.2016.14.2.152

Abstract PDF Supplementary Material PubReader ePub

<b>Background/Aims</b><br/>

This was a Phase 2 study (NCT02015793) to evaluate the pharmacokinetics, safety, and efficacy of adalimumab in Chinese patients with Crohn's disease (CD).

Methods

Thirty, adult Chinese patients with CD (CD Activity Index [CDAI] 220–450; high-sensitivity [hs]-C-reactive protein [CRP] ≥3 mg/L) received double-blind adalimumab 160/80 mg or 80/40 mg at weeks 0/2, followed by 40 mg at weeks 4 and 6. An open-label extension period occurred from weeks 8–26; patients received 40 mg adalimumab every other week. Serum adalimumab concentration and change from baseline in fecal calprotectin (FC) were measured during the double-blind period. Clinical remission (CDAI <150), response (decrease in CDAI ≥70 points from baseline), and change from baseline in hs-CRP were assessed through week 26. Nonresponder imputation was used for missing categorical data and last observation carried forward for missing hs-CRP/FC values. No formal hypothesis was tested. Adverse events were monitored.

Results

Mean adalimumab serum concentrations during the induction phase were 13.9–18.1 µg/mL (160/80 mg group) and 7.5−9.5 µg/mL (80/40 mg group). During the double-blind period, higher remission/response rates and greater reductions from baseline in hs-CRP and FC were observed with adalimumab 160/80 mg compared to that with 80/40 mg. Adverse event rates were similar among all treatment groups.

Conclusions

Adalimumab serum concentrations in Chinese patients with CD were comparable to those observed previously in Western and Japanese patients. Clinically meaningful remission rates and improvement in inflammatory markers were achieved with both dosing regimens; changes occurred rapidly with adalimumab 160/80 mg induction therapy. No new safety signals were reported.

Citations

Citations to this article as recorded by

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