A systematic review and meta-analysis of artificial intelligence-diagnosed endoscopic remission in ulcerative colitis

Abstract

Summary: Endoscopic remission is an important therapeutic goal in ulcerative colitis (UC). The Ulcerative Colitis Endoscopic Index of Severity (UCEIS) and Mayo Endoscopic Score (MES) are the commonly used endoscopic scoring criteria. This systematic review and meta-analysis aimed to evaluate the accuracy of artificial intelligence (AI) in diagnosing endoscopic remission in UC. We also performed a meta-analysis of each of the four endoscopic remission criteria (UCEIS = 0, MES = 0, UCEIS = <1, MES = <1). Eighteen studies involving 13,687 patients were included. The combined sensitivity and specificity of AI for diagnosing endoscopic remission in UC was 87% (95% confidence interval [CI]:81–92%) and 92% (95% CI: 89–94%), respectively. The area under the curve (AUC) was 0.96 (95% CI: 0.94–0.97). The results showed that the AI model performed well regardless of which criteria were used to define endoscopic remission of UC.

Keywords

• Pathophysiology
• Artificial intelligence