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TRV-2026-0679Certified recordPeer-reviewed

The Role of Artificial Intelligence Combined With Digital Cholangioscopy for Indeterminant and Malignant Biliary Strictures: A Systematic Review and Meta-analysis

Background Current endoscopic retrograde cholangiopancreatography (ERCP) and cholangioscopic-based diagnostic sampling for indeterminant biliary strictures remain suboptimal. Artificial intelligence (AI)-based algorithms by means of computer vision in machine learning have been applied to cholangioscopy in an effort to improve diagnostic yield. The aim of this study was to perform a systematic review and meta-analysis to evaluate the diagnostic performance of AI-based diagnostic performance of AI-associated chol…

Health · G Space — documented gain · certified 2026-08-07 · v1 · article view · machine-readable

Current reading — gain

AI-based machine learning applied to cholangioscopy images achieved high pooled diagnostic performance for indeterminate and malignant biliary strictures, with 95% sensitivity and 88% specificity.

What this doesn’t fix

Evidence base is limited to five studies with 675 lesions, indicating early-stage evaluation rather than broad clinical validation.

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Truvace Impact Record TRV-2026-0679, v1: “The Role of Artificial Intelligence Combined With Digital Cholangioscopy for Indeterminant and Malignant Biliary Strictures: A Systematic Review and Meta-analysis.” Truvace, 2026-08-07. /record/TRV-2026-0679 (accessed at citation time). sha256 c243d62976ad879b…

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