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1. Background and Rationale The visual diagnosis of peri-implant mucosal erythema (redness), a key sign of inflammation, is highly subjective and varies significantly among clinicians, leading to inconsistencies in early detection and monitoring of peri-implant diseases. There is a critical need for an objective, quantitative, and reliable tool to standardize this assessment. Recent advances in artificial intelligence (AI) and colorimetric analysis of digital intraoral scans offer a promising solution to this clinical challenge. 2. Primary Objectives This diagnostic study aims to: Develop and validate a core colorimetric index that objectively quantifies mucosal erythema from digital intraoral scan data. Develop and validate an AI model that automatically calculates this index and provides a binary diagnosis (erythema present/absent) at the image level. Develop and valida
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