Evaluation of Artificial Intelligence Models for Diagnosi... | NCT06140849

Studies
Evaluation of Artificial Intelligence Models for Diagnosis of Anterior Open Bite Malocclusion

NCT06140849

Sponsor

Cairo University

Status

Unknown status

Last Update Posted

Nov 20, 2023Actual

Enrollment

200Estimated

Phase

Not provided

Conditions

Artificial Intelligence
Open Bite

Interventions

artificial intelligence model

Countries

Egypt

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Nov 2023

Overall Recruitment Status or Expanded Access Status

Unknown status

Last Known Status

Recruiting

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Nov 2023Estimated

Primary Completion Date

Jul 2024Estimated

Completion Date

Sep 2024Estimated

First Submitted Date

Nov 15, 2023

First Submission Date that Met QC Criteria

Nov 19, 2023

First Posted Date

Nov 20, 2023Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Nov 19, 2023

Last Update Posted Date

Nov 20, 2023Actual

Sponsor/Collaborators Module

Responsible Party, by Official Title

Heba El-Sayed Kamel Akl, Lecturer at Orthodontic Department- Faculty of Dentistry, Cairo UniversityPrincipal Investigator

Lead Sponsor

Cairo UniversityOTHER

Collaborators

Name	Class
Future University in Egypt	OTHER

Oversight Module

Has Data Monitoring Committee (DMC)

Yes

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

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.

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Target Follow-Up Duration

Not provided

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

200Estimated

Arms/Interventions Module

Arm Groups

Not provided

Interventions

Name	Type	Description	Arm Group Labels	Other Names
artificial intelligence model	Diagnostic Test	artificial intelligence model of anterior open bite diagnosis

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
the efficiency of artificial intelligence (AI) model in diagnosis of anterior open bite	The percentage of agreement between the AI model result and the actual diagnosis	8 months

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

anterior open bite

Exclusion Criteria:

craniofacial syndromes, previous orthodontic treatment, poor quality records

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

7 Years

Maximum Age

60 Years

Standard Ages

ChildAdult

Study Population

Any patient with anterior open bite of any type and severity will be included in the study

Sampling Method

Probability Sample

Contacts/Locations Module

Central Contacts

Name	Role	Phone	Extension	Email
Heba Akl, BDS, MSc., PhD	Contact	+201227418915		heba.akl@dentistry.cu.edu.eg

Overall Officials

Name	Affiliation	Role
Yehya Mostafa, DDS., PhD	Cairo	Study Director

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Orthodontic Department, Faculty of Dentistry, Cairo University	Recruiting	Cairo		11451	Egypt

IPD Sharing Statement Module

Plan to Share IPD

Undecided

Description

Not provided

Types

Not provided

Time Frame

Not provided

Access Criteria

Not provided

URL

Not provided

Condition Browse Module

MeSH Terms

ID	Term
D024343	Open Bite

Ancestor Terms

ID	Term
D008310	Malocclusion
D014076	Tooth Diseases
D009057	Stomatognathic Diseases

Browse Leaves

Not provided

Browse Branches

Not provided