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

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

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

Inclusion Criteria:

cases of non-growing patients with class II malocclusion

Exclusion Criteria:

Growing patient with class II malocclusion