Evaluating the potential of artificial intelligence in ulcerative colitis

Introduction: Diagnosis and therapeutic management in ulcerative colitis (UC) relies on a combination of endoscopic and histological scorings which are difficult to objectively quantify. Artificial intelligence (AI) might overcome the current issues of inter-observer variability, repetitive need for biopsies and estimation of disease activity medicine currently encourages. Areas covered: With this narrative literature review we aim to provide a clear and critical overview of the recent evolutions in the field of AI and UC, based on a literature search performed on Pubmed, Embase and Cochrane Library. The major focus of this review is the use of AI for endoscopic assessment of disease activity and the correlation with histology and long-term outcome. Moreover, we elucidate on the more recent developments in the field of AI as support in histological disease assessment, surveillance, therapy monitoring and natural language processing. Expert opinion: UC management is evolving with AI impacting nearly every aspect of it. The immediate future influence of AI in UC management will be focussed on the collection, extraction and organization of particular clinical information. Expect is the transformation toward a real-time standardized, reproducible, objective and high-reliable disease grading, especially in endoscopy, histology and eventually radiology applications for UC.

Automated summary

Diagnosis and therapeutic management in ulcerative colitis rely on difficult-to-quantify endoscopic and histological scorings. Artificial intelligence (AI) can overcome issues of variability and estimation of disease activity. This review provides an overview of recent developments in AI for UC, with a focus on endoscopic assessment, histology correlation, and other applications such as surveillance and therapy monitoring.