ASGE International Sampler (On-Demand)-THRIVING WITH ARTIFICIAL INTELLIGENCE (AI) IN ENDOSCOPY - PRACTICAL TIPS AND TRICKS IN OPTIMIZING AI-GUIDED COLONOSCOPY IN REAL-TIME POLYP IDENTIFICATION AND CHARACTERIZATION

THRIVING WITH ARTIFICIAL INTELLIGENCE (AI) IN ENDOSCOPY - PRACTICAL TIPS AND TRICKS IN OPTIMIZING AI-GUIDED COLONOSCOPY IN REAL-TIME POLYP IDENTIFICATION AND CHARACTERIZATION

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Video Transcription

Video Summary

Artificial Intelligence (AI) is enhancing colonoscopy by improving lesion detection rates. The integration of AI technology in endoscopy systems has shown benefits such as increased polyp and adenoma detection, leading to early colorectal cancer diagnosis. Despite AI's potential, there is a lack of standardised guidance on optimising AI programs. Challenges like null predictions can be addressed through improved visualisation, extended analysis duration, and repeat lesion analysis. Endoscopists should not solely rely on AI for detecting malignant lesions. Sharing techniques among endoscopists can improve AI algorithms. While AI aids in colonoscopy, clinical judgment remains crucial for identifying suspicious lesions.

Asset Subtitle

Gabrielle Eloise Ming Yen Koh

Meta Tag

Concept AI-guided colonoscopy

Concept Colorectal Polyp Detection

Concept Adenoma Detection

Concept Lesion Characterization

Concept Cancerous Lesion

Keywords

Artificial Intelligence

colonoscopy

lesion detection

endoscopy

colorectal cancer

AI-guided colonoscopy

Colorectal Polyp Detection

Adenoma Detection

Lesion Characterization

Cancerous Lesion