Evaluation of Diagnostic Accuracy of Artificial Intelligence in Treatment Planning for Non-growing Class II Cases

Not yet recruiting

• Conditions: Class II Malocclusion

• Registration Number: NCT06792747
• Lead Sponsor: Cairo University

Brief Summary

The goal of this observational study is to evaluate the diagnostic accuracy of artificial intelligence in non-growing class II cases. The main question it aims to answer is:

Is Artificial Intelligence (AI) accurate in choosing a treatment modality for non-growing class II cases -whether to camouflage or surgical treatment?

participants already undergone orthodontic treatment, their pre-treatment and post-treatment records will be collected from the archive of orthodontic department at Cairo university

Detailed Description

Not available

Study Timeline

• Status Verified: 2024-01
• Study Start: 2025-01
• Study First Submitted: 2025-01-20
• Study First Submitted QC: 2025-01-20
• Last Update Submitted: 2025-01-20
• Study First Posted: 2025-01-27
• Last Update Posted: 2025-01-27
• Primary Completion: 2025-06
• Study Completion: 2025-12

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 193

Inclusion Criteria

cases of non-growing patients with class II malocclusion

Exclusion Criteria

Growing patient with class II malocclusion

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Accuracy of Artificial intelligence in choosing\predicting the best treatment modality	from enrollment to the end of treatment at 1 year