Official title: A Diagnostic Study to Develop and Validate an Artificial Intelligence-Based Colorimetric System for the Objective Diagnosis of Peri-Implant Mucosal Erythema and to Evaluate Its Impact on Clinician Performance Summary: 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 validate a second AI model for precise localization (object detection) of erythematous regions on standard clinical software screenshots.
ClinicalTrials.gov published a clinical update in Critical Care on 16 Jan 2026.
The item focuses on AI-Assisted Colorimetric Diagnosis of Peri-Implant Mucosal Erythema.
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