Correct endoscopic prediction of the histopathology and differentiation between benign, pre-malignant, and malignant colorectal polyps (optical diagnosis) remains difficult. Artificial intelligence has great potential in image analysis in gastrointestinal endoscopy. Aim of this study is to investigate the real-time diagnostic performance of AI4CRP for the classification of diminutive colorectal polyps, and to compare it with the real-time diagnostic performance of commercially available CADx systems.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Technical feasibility of real-time use of AI4CRP.
Timeframe: 6 months
User interface feasibility of real-time use of AI4CRP.
Timeframe: 6 months
The diagnostic accuracy of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
Timeframe: 1 year
The sensitivity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
Timeframe: 1 year
The specificity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
Timeframe: 1 year
The negative predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
Timeframe: 1 year
The positive predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
Timeframe: 1 year
The Area Under ROC Curve (AUC) of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
Timeframe: 1 year
Quirine van der Zander, Drs MD