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

Status

Not yet recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT06792747

Enrollment

193

Registered

2025-01-27

Start date

2025-01-31

Completion date

2025-12-31

Last updated

2025-01-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Class II Malocclusion

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

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

Yes

Inclusion criteria

cases of non-growing patients with class II malocclusion

Exclusion criteria

Growing patient with class II malocclusion

Design outcomes

Primary

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

Contacts

Primary ContactIsraa abuobieda elbagari, Msc candidate

israa.ibrahim@dentistry.cu.edu.eg+201129684395

Backup Contactisraa abuobieda elbagari, Msc candidate

iskyme722@gmail.com+201129684395

Outcome results