Evaluation of Artificial Intelligence Models for Diagnosis of Anterior Open Bite Malocclusion
Trial Snapshot
- Phase
- Not Applicable
- Status
- Recruiting
- Sponsor
- Cairo University
- Enrollment
- 200
- Locations
- 1
- Primary Endpoint
- the efficiency of artificial intelligence (AI) model in diagnosis of anterior open bite
Study Overview
Brief Summary
Building artificial intelligence models for diagnosis of anterior open bite malocclusion
Detailed Description
The study aims at creating artificial intelligence models, with the input being the pre-treatment photographs and radiographs of open bite patients that are routinely taken for diagnosis and treatment planning. The output of the AI model will be the type and phenotype of anterior open bite. The photographs and radiographs with highest quality will be arranged in certain standardized templates to facilitate the machine learning process.
Study Design
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Prospective
Eligibility Criteria
- Ages
- 7 Years to 60 Years (Child, Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •anterior open bite
Exclusion Criteria
- •craniofacial syndromes, previous orthodontic treatment, poor quality records
Outcomes
Primary Outcomes
the efficiency of artificial intelligence (AI) model in diagnosis of anterior open bite
Time Frame: 8 months
The percentage of agreement between the AI model result and the actual diagnosis
Secondary Outcomes
No secondary outcomes reported
Investigators
Heba El-Sayed Kamel Akl
Lecturer at Orthodontic Department- Faculty of Dentistry
Cairo University