Clinical applications of artificial intelligence and machine learning-based methods in inflammatory bowel disease

Area of Science:

• Medical Informatics
• Artificial Intelligence in Medicine
• Gastroenterology

Background:

• Inflammatory bowel disease (IBD) presents complex challenges with significant variations in patient care and outcomes.
• Artificial intelligence (AI) offers a promising avenue to address these complexities and standardize healthcare delivery.
• The integration of AI in IBD management is crucial for improving patient care quality.

Purpose of the Study:

• To review and exemplify AI applications that can improve inflammatory bowel disease (IBD) care.
• To identify current gaps and future research directions for AI in IBD.
• To highlight AI's potential to reduce healthcare variations and enhance patient outcomes.

Main Methods:

• Literature review of selected AI applications in IBD.
• Exemplification of AI's role in IBD pathogenesis, diagnosis, and prognosis.
• Analysis of AI's capabilities in mimicking human intelligence for clinical decision-making.

Main Results:

• AI applications show potential in studying IBD pathogenesis, diagnosis, and prognosis.
• AI can aid in reducing variability in IBD healthcare delivery.
• Early-stage AI development in IBD demonstrates significant potential for future transformation.

Conclusions:

• AI holds immense potential to revolutionize inflammatory bowel disease (IBD) care.
• Addressing current research gaps will accelerate the adoption of AI in IBD.
• AI can lead to more consistent and improved patient outcomes in IBD management.