**3.5 AI in IBD diagnostics**

AI has also been explored widely in IBD diagnosis. The need for AI in identifying IBD and correctly identifying the type of Crohn's disease and ulcerative colitis has been pointed out by Suandram et al. The problem with diagnosing IBD through endoscopy is the subjectivity of the endoscopist in interpreting the results rather than the endoscopic result visualization. To aid in the decision-making, making AI-based applications exist, such as computer-aided diagnosis (CADx). The works reviewed by Suneha et al. have shown great accuracy in detecting and differentiating IBM diseases. Mossotto, 2017 was able to classify UC and Crohn's disease with an accuracy of 83.3% using pediatric data involving endoscopic images and histology [88]. Barash,


### **Table 1.**

*AI applications summary in GI tract autoimmune diseases.*

2021 was able to diagnose CD ulcer severity with great accuracy based on capsule endoscopy images [89]. On the other hand, Gottlieb, 2020 used an endoscopy video to the grade the UC severity [90]. Takenaka, 2020 predicted the UC remission with 90% accuracy using endoscopic images and histology [91]. For detailed reviewing of AI in IBD, we refer the reader to in-scope reviews (**Table 1**) [92–101].
