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KI - Künstliche Intelligenz

21-02-2024 | Project Reports

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

Authors: Bjørn Leth Møller, Bobby Zhao Sheng Lo, Johan Burisch, Flemming Bendtsen, Ida Vind, Bulat Ibragimov, Christian Igel

Published in: KI - Künstliche Intelligenz

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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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Metadata
Title
Building an AI Support Tool for Real-Time Ulcerative Colitis Diagnosis
Authors
Bjørn Leth Møller
Bobby Zhao Sheng Lo
Johan Burisch
Flemming Bendtsen
Ida Vind
Bulat Ibragimov
Christian Igel
Publication date
21-02-2024
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-023-00820-x

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