- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06002373
Assessment of Artificial Intelligence for Treatment Decision Recommendation of Adult Skeletal Class III Patients
Reliability Of Artificial Intelligence for Treatment Decision Recommendation of Adult Skeletal Class III Patients: A Diagnostic Test Accuracy Study
The study titled "Reliability Of Artificial Intelligence for Treatment Decision Recommendation of Adult Skeletal Class III Patients" aims to assess the accuracy and dependability of artificial intelligence (AI) in providing treatment decision recommendations for adult patients with skeletal Class III malocclusion. Skeletal Class III malocclusion is characterized by an underdeveloped upper jaw or an overdeveloped lower jaw, leading to facial and dental irregularities. The study focuses on evaluating whether AI-based recommendations can reliably guide orthodontic treatment planning for this specific patient group.
This diagnostic test accuracy study involves collecting a diverse dataset of adult patients diagnosed with skeletal Class III malocclusion. AI algorithms will be trained on this dataset using various clinical and radiographic parameters to learn patterns and make treatment recommendations. The study will then compare the AI-generated treatment recommendations to those provided by experienced orthodontists.
Key aspects of the study include:
AI Reliability: The primary objective is to assess how consistently and accurately the AI system can recommend appropriate treatment decisions for adult skeletal Class III patients.
Diagnostic Test Accuracy: The study will determine the sensitivity, specificity, positive predictive value, and negative predictive value of the AI-generated treatment recommendations. This analysis will highlight the AI's ability to correctly identify patients who require specific treatment interventions.
Clinical Validity: Researchers will investigate whether the AI recommendations align with the decisions made by experienced orthodontists. This assessment is crucial to establish the AI system's clinical applicability.
Potential Benefits: If the AI system proves reliable and accurate, it could offer a time-efficient and standardized method for treatment decision support, aiding orthodontists in providing personalized care to adult skeletal Class III patients.
By conducting this study, researchers aim to contribute to the advancement of AI-assisted medical decision-making within the field of orthodontics. Successful outcomes would have the potential to revolutionize treatment planning processes, improve patient outcomes, and provide a valuable tool for orthodontists to make informed treatment decisions for adult skeletal Class III patients
Study Overview
Status
Conditions
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Contact
- Name: Maha AM Swelam, PhD
- Phone Number: 00201123344551
- Email: maha.swelam@gmail.com
Study Locations
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-
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Cairo, Egypt
- Recruiting
- Cairo University
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Contact:
- Abd El Rahim
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Skeletally mature patients with CVMI 6.
- Skeletal class III patients
- No congenital deformity, syndrome, or cleft.
- No previous surgical intervention
- No mandibular transverse functional shift.
- Normal overjet, overbite after completion of treatment.
- Patients with well finished occlusion.
- Patients who have achieved adequate functional and aesthetic results at the end of their treatment.
- Good quality initial and final lateral cephalometric radiographs.
- No sex predilection.
Exclusion Criteria:
- Adolescents and skeletally immature patients.
- Patients with pseudo class III.
- Syndromic patients.
- Patients with facial deformity at the naso-maxillary complex
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
sensitivity and specificity
Time Frame: 1 month
|
the difference in sensitivity and specificity between the treatment decisions taken by the clinicians in comparison to those provided by the artificial intelligence software
|
1 month
|
Collaborators and Investigators
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 8114
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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