Artificial Intelligence in Advancing Inflammatory Bowel Disease Management: Setting New Standards

Area of Science:

• Gastroenterology
• Medical Informatics
• Artificial Intelligence

Background:

• Artificial intelligence (AI) is increasingly utilized to enhance the diagnosis and management of inflammatory bowel disease (IBD).
• AI applications in IBD endoscopy are rapidly evolving, impacting clinical practice.

Purpose of the Study:

• To conduct a narrative review of AI applications in IBD endoscopy.
• Focus on AI's role in diagnosis, disease activity assessment, therapy prediction, and dysplasia detection.

Main Methods:

• Literature review of AI applications in IBD endoscopy.
• Analysis of studies evaluating AI for diagnosis, disease activity, treatment response, and dysplasia detection.

Main Results:

• AI systems achieve high accuracy in assessing endoscopic and histological disease activity in ulcerative colitis and Crohn's disease, comparable to experts.
• Machine learning models predict treatment response and complication risk; AI aids real-time histology and dysplasia detection.
• Challenges include the need for larger datasets, external validation, and bias mitigation.

Conclusions:

• AI holds significant potential to improve IBD care through objective assessments, outcome prediction, and enhanced surveillance.
• Further validation in diverse populations and prospective studies are required for clinical integration.
• Addressing regulatory and cost barriers is crucial for AI's successful implementation in IBD management.