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Building an AI Support Tool for Real-Time Ulcerative Colitis Diagnosis

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Abstract

Ulcerative Colitis (UC) is a chronic inflammatory bowel disease decreasing life quality through symptoms such as bloody diarrhoea and abdominal pain. Endoscopy is a cornerstone of diagnosis and monitoring of UC. The Mayo endoscopic subscore (MES) index is the standard for measuring UC severity during endoscopic evaluation. However, the MES is subject to high inter-observer variability leading to misdiagnosis and suboptimal treatment. We propose using a machine-learning based MES classification system to support the endoscopic process and to mitigate the observer-variability. The system runs real-time in the clinic and augments doctors’ decision-making during the endoscopy. This project report outlines the process of designing, creating and evaluating our system. We describe our initial evaluation, which is a combination of a standard non-clinical model test and a first clinical test of the system on a real patient.

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Data availability

The patient data that support the findings of this study are not openly available due to reasons of sensitivity.

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Acknowledgements

We acknowledge support from the Gastro Unit, medical section, Copenhagen University Hospital Hvidovre, which made this research possible. We thank the Novo Nordisk Foundation for aiding our research with financial support under Grant NNF20OC0062056. Finally, we thank BETA.HEALTH for supporting our goal to bring our research into clinical practice under Grant no. 1260.

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Author notes

  1. Bjørn Leth Møller and Bobby Zhao Sheng Lo contributed equally to this work.

Authors and Affiliations

  1. Department of Computer Science, University of Copenhagen, Copenhagen, Denmark

    Bjørn Leth Møller, Bulat Ibragimov & Christian Igel

  2. Gastrounit, Medical Section, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark

    Bobby Zhao Sheng Lo, Johan Burisch, Flemming Bendtsen & Ida Vind

  3. Copenhagen IBD Center, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark

    Bobby Zhao Sheng Lo, Johan Burisch, Flemming Bendtsen & Ida Vind

Authors
  1. Bjørn Leth Møller
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  2. Bobby Zhao Sheng Lo
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  4. Flemming Bendtsen
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  7. Christian Igel
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Corresponding author

Correspondence to Bjørn Leth Møller.

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Conflict of interest

Bobby Lo reports an unrestricted grant from Beta. Health related to the submitted work and advisory/consultant fee from Tillotts Pharma, Bristol-Myers Squibb, Paratech A/S; Teaching fee from Tillotts Pharma, Janssen Cilag; Research grant from Tillotts Pharma, Janssen Cilag, Takeda, Abbvie. Dr. Burisch reports grants and personal fees from AbbVie, grants and personal fees from Janssen-Cilag, personal fees from Celgene, grants and personal fees from MSD, personal fees from Pfizer, grants and personal fees from Takeda, grants and personal fees from Tillots Pharma, personal fees from Samsung Bioepis, grants and personal fees from Bristol Myers Squibb, grants from Novo Nordisk, personal fees from Pharmacosmos, personal fees from Ferring, personal fees from Galapagos, outside the submitted work. Doctor Bendtsen reports consulting fees, lecture fees or research funds from Takeda Pharma A/S, Norgine Danmark A/S, Ferring Pharmaceuticals A/S. No other authors have anything to report.

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Møller, B.L., Lo, B.Z.S., Burisch, J. et al. Building an AI Support Tool for Real-Time Ulcerative Colitis Diagnosis. Künstl Intell 38, 169–176 (2024). https://doi.org/10.1007/s13218-023-00820-x

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  • DOI: https://doi.org/10.1007/s13218-023-00820-x

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