Colonoscopy

Artificial intelligence (AI) has the potential to change many aspects of health-care practice. Two newly published trials explore the potential applications of AI to improve polyp detection and mucosal visualization in gastrointestinal endoscopy — both show the benefits of AI to improve detection in gastrointestinal endoscopy.

A deep-learning algorithm enables the real-time video-based recognition of polyps during colonoscopy, with sensitivities and specificities surpassing 90%.

In a recent study, Kawada et al. conducted a retrospective analysis of paediatric patients who had undergone lower gastrointestinal endoscopy to evaluate its use as a diagnostic tool. This under-studied area deserves critique within a modern framework of expectation for the routine yield for this invasive investigation in standard paediatric gastroenterology practice.

The interval colorectal cancer rate is a robust indicator of the quality and effectiveness of a screening programme, enabling the identification of unmet requirements and development of specific strategies to resolve them. A recent study demonstrated the use of interval cancer as an indicator to target quality improvement of colonoscopy in a screening programme.