Artifical Intelligence, Gummy Smile
Conditions
Brief summary
Some people have a "gummy smile," where too much gum tissue shows when they smile. Doctors currently diagnose this by hand, using rulers and visual judgment. This study is testing whether a computer program using artificial intelligence (AI) can help identify and measure gummy smiles from photographs, as accurately as expert dentists do it manually. Patients seen at Cairo University's Periodontics and Orthodontics clinics will have photos of their smile taken. Researchers will use these photos to first "teach" the AI program how to recognize and measure a gummy smile. Then, the AI will be tested on a new set of patient photos, and its measurements will be compared to measurements made by expert dentists, to see how closely they match. The goal is to find out whether this AI tool could one day help doctors diagnose gummy smiles more quickly and consistently, which may improve care for patients.
Detailed description
This is a diagnostic accuracy test to evaluate the accuracy of decisions made by the computer generated program in the cases of gummy smile compared to the conventional decisions made by the periodontist as a gold standard.
Interventions
None listed
Sponsors
Cairo University
Study design
Observational model
OTHER
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Inclusion criteria
* Properly treated gummy smile cases either surgical through crown lengthening procedure / Orthognathic Surgery or non-surgical through orthodontic treatment /Botox injection.
Exclusion criteria
* Improperly treated gummy smile cases
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic Accuracy of AI Software | During the Validation phase (Months 5-6) and Post-analytical phase (Months 7-8) of the study, when the AI model's measurements are tested against the reference standard | The primary outcome of the study is the diagnostic accuracy of the AI software. This metric will assess the ability of the software to accurately identify cases of gummy smile compared to traditional diagnostic methods. The results will be measured and reported as a percentage, providing a clear indication of the software's performance and reliability in clinical settings. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Effectiveness of treatment planning of AI Software | Months 5 through 8 of the study (Validation and Post-analytical phases), during which the AI model's measurements are compared against the reference standard | The secondary outcome of the study is the effectiveness of the treatment planning generated by the AI software. This metric will examine how well the software formulates treatment plans for cases of gummy smile in comparison to conventional methods used by periodontists. The effectiveness will be quantified and reported as a percentage, allowing for an assessment of the AI's ability to propose viable and successful treatment options. By focusing on treatment planning, this outcome aims to highlight the potential of AI technology to improve clinical decision-making and patient outcomes in periodontal care |
Countries
Egypt
Contacts
CONTACTHesham Ahmed Shamma, BDS
Outcome results
None listed