Article

Beyond Binary: Four-Class Risk Stratification from Gastrointestinal Endoscopy Using Asymmetric-Cost Lightweight CNN–Transformer Learning

2026-07-28

Abstract excerpt

<title>Abstract</title> <p>Gastrointestinal cancers account for more than 3.5 million deaths annually, yet existing AI-assisted endoscopy systems reduce the clinical decision to a binary lesion-present/absent output misaligned with published clinical practice guidelines. We present a lightweight CNN–Transformer benchmark for four-class gastrointesti- nal lesion risk stratification aligned with American College of...

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Literature Corpus work: bc6af72c-a546-5688-adee-178c2f3dd4c6
DOI: 10.21203/rs.3.rs-10475241/v1

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