Mandibular AsymmetryNCT07197359
Looksmaxxing AI for Chin Deviation Detection
An observational study of Mandibular Asymmetry, run by Konya Necmettin Erbakan Üniversitesi at 1 site in Turkey (Türkiye).
Trial summary
This study aims to evaluate whether an artificial intelligence application called Looksmaxxing AI will be able to correctly identify chin deviation (chin asymmetry) from standard frontal facial photographs. A total of 540 photographs will be included in the study. The eye areas will be covered to protect identity. Read more about this study
- Who is it for?
- Ages 10 to 40 yearsHealthy volunteers can take part
- Conditions the study is for
- Mandibular Asymmetry
- What is being tested?
- Looksmaxxing AI Facial Analysis
- How many people
- 90 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 1 Sep 2025to 15 Oct 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 10 to 40 years
- All sexes
- Healthy volunteers accepted
- Child, Adult
Study population: Standardized frontal facial photographs of 90 individuals (540 images in total) will be analyzed. The study population consists of two equal groups: 270 photographs from individuals with clinically observed chin deviation (laterognathia) and 270 photographs from individuals with clinically normal chin position.
Who may be able to join
- Absence of any craniofacial anomaly
- No major wound or scar in the facial or neck region
- No history of previous orthodontic treatment
- For male participants: absence of a long beard that could affect the appearance of the chin
- Availability of standardized frontal facial photographs taken in natural head position
Who cannot join
- Photographs in which the patient's face appears slightly angled or turned sideways
- Blurred or low-quality photographs with reduced clarity
Trial locations and contacts
1 site in 1 country.
Turkey (Türkiye)1 site
Necmettin Erbakan University
Konya, Konya, 42090
About this study
Official title: Detecting Asymmetry With Artificial Intelligence: Consistency Evaluation of the Looksmaxxing Application in Photo-Based Facial Analysis
This study aims to evaluate whether an artificial intelligence application called Looksmaxxing AI will be able to correctly identify chin deviation (chin asymmetry) from standard frontal facial photographs. A total of 540 photographs will be included in the study. The eye areas will be covered to protect identity. Each photo will be analyzed by the AI, and its answers will be compared with clinical reality. The accuracy of two versions of the software (Looksmaxxing 4o and 5) will be assessed. The results may help show whether simple photo-based analysis can support early detection of chin asymmetry, especially in areas with limited access to orthodontic examination.
Read the detailed description
This observational study will investigate the accuracy of the Looksmaxxing AI application in detecting chin deviation based on standardized frontal facial photographs. A total of 540 images will be included. To protect identity, the eye areas of all participants will be covered. The AI will be asked to determine whether chin deviation is present relative to the midline of the face (excluding the nose).
The study population will consist of two equally sized groups:
270 individuals with clinically observed chin deviation (laterognathia)
270 individuals with clinically normal chin position
The responses provided by Looksmaxxing AI will be compared with the clinical reality and recorded for accuracy. Both versions of the software, Looksmaxxing 4o and Looksmaxxing 5, will be analyzed to evaluate their level of consistency with clinical findings. Results will be reported as accuracy percentages. In addition, prediction accuracy will be compared between individuals with and without chin deviation, and the statistical significance of the difference will be tested using the Chi-square method.
- Conditions
- Mandibular Asymmetry
- Being tested
- Looksmaxxing AI Facial Analysis
- Keywords
- chin asymmetry, photographic analysis, artificial intelligence
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Looksmaxxing AI Facial AnalysisOther
Participants' standardized frontal facial photographs will be analyzed using the Looksmaxxing AI application (versions 4o and 5) to determine the presence or absence of chin deviation relative to the facial midline.
| Study group | Role | What they receive |
|---|---|---|
| With Chin Deviation | Participants clinically diagnosed with chin deviation (laterognathia) based on frontal facial examination. Receives: Other: Looksmaxxing AI Facial Analysis | |
| Without Chin Deviation | Participants with clinically normal chin position confirmed by frontal facial examination. Receives: Other: Looksmaxxing AI Facial Analysis |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of Looksmaxxing AI in Detecting Chin Deviation
The proportion of correct classifications (presence or absence of chin deviation) made by the Looksmaxxing AI application compared to the clinical gold standard, expressed as a percentage.
Measured: At study completion (October 2025)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Sep 2025
- Study start1 Sep 2025
- Primary completion30 Sep 2025 (estimated)
- Study completion15 Oct 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Mandibular AsymmetryStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 90 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Konya Necmettin Erbakan Üniversitesi
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Seda Sağoğlu, Konya Necmettin Erbakan Üniversitesi
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07197359
- Sponsor's protocol ID
- 2025/635
- Status last verified
- Sep 2025
- First submitted
- 21 Sep 2025
- Last updated
- 2 Oct 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data (facial photographs) will not be shared due to privacy concerns and the risk of re-identification. Only aggregated and anonymized results will be published.
Study at a glance
From the registry record, last updated by the sponsor on 2 Oct 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Detecting Asymmetry With Artificial Intelligence: Consistency Evaluation of the Looksmaxxing Application in Photo-Based Facial Analysis
- ClinicalTrials.gov ID
- NCT07197359
- Acronym / sponsor ID
- 2025/635
- Conditions
- Mandibular Asymmetry
- Keywords
- chin asymmetry, photographic analysis, artificial intelligence
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 90 participants (estimated)
- Lead sponsor
- Konya Necmettin Erbakan ÜniversitesiUniversity, hospital or other
- Study start
- 1 Sep 2025 (actual)
- Primary completion
- 30 Sep 2025 (estimated)
- Study completion
- 15 Oct 2025 (estimated)
- First posted
- 29 Sep 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study aims to evaluate whether an artificial intelligence application called Looksmaxxing AI will be able to correctly identify chin deviation (chin asymmetry) from standard frontal facial photographs. A total of 540 photographs will be included in the study. The eye areas will be covered to protect identity. Each photo will be analyzed by the AI, and its answers will be compared with clinical reality. The accuracy of two versions of the software (Looksmaxxing 4o and 5) will be assessed. The results may help show whether simple photo-based analysis can support early detection of chin asymmetry, especially in areas with limited access to orthodontic examination.
Detailed description
This observational study will investigate the accuracy of the Looksmaxxing AI application in detecting chin deviation based on standardized frontal facial photographs. A total of 540 images will be included. To protect identity, the eye areas of all participants will be covered. The AI will be asked to determine whether chin deviation is present relative to the midline of the face (excluding the nose).
The study population will consist of two equally sized groups:
270 individuals with clinically observed chin deviation (laterognathia)
270 individuals with clinically normal chin position
The responses provided by Looksmaxxing AI will be compared with the clinical reality and recorded for accuracy. Both versions of the software, Looksmaxxing 4o and Looksmaxxing 5, will be analyzed to evaluate their level of consistency with clinical findings. Results will be reported as accuracy percentages. In addition, prediction accuracy will be compared between individuals with and without chin deviation, and the statistical significance of the difference will be tested using the Chi-square method.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| With Chin Deviation | – | Other: Looksmaxxing AI Facial AnalysisParticipants clinically diagnosed with chin deviation (laterognathia) based on frontal facial examination. |
| Without Chin Deviation | – | Other: Looksmaxxing AI Facial AnalysisParticipants with clinically normal chin position confirmed by frontal facial examination. |
Who may qualify
- Ages
- 10 to 40 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult
- Study population
- Standardized frontal facial photographs of 90 individuals (540 images in total) will be analyzed. The study population consists of two equal groups: 270 photographs from individuals with clinically observed chin deviation (laterognathia) and 270 photographs from individuals with clinically normal chin position.
Key inclusion criteria (5 listed)
- Absence of any craniofacial anomaly
- No major wound or scar in the facial or neck region
- No history of previous orthodontic treatment
- For male participants: absence of a long beard that could affect the appearance of the chin
- Availability of standardized frontal facial photographs taken in natural head position
Key exclusion criteria (2 listed)
- Photographs in which the patient's face appears slightly angled or turned sideways
- Blurred or low-quality photographs with reduced clarity
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Looksmaxxing AI Facial AnalysisParticipants' standardized frontal facial photographs will be analyzed using the Looksmaxxing AI application (versions 4o and 5) to determine the presence or absence of chin deviation relative to the facial midline. | Other | With Chin Deviation, Without Chin Deviation |
Primary outcome
Accuracy of Looksmaxxing AI in Detecting Chin Deviation
Time frame: At study completion (October 2025)
The proportion of correct classifications (presence or absence of chin deviation) made by the Looksmaxxing AI application compared to the clinical gold standard, expressed as a percentage.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Oct 2025.
- This article reports the use of deep learning for automatic classification of orthodontic photographs, providing methodological background relevant to AI-based facial asymmetry detection.Link provided by the sponsor.
- Individual participant dataSharing planned: No. Individual participant data (facial photographs) will not be shared due to privacy concerns and the risk of re-identification. Only aggregated and anonymized results will be published.
Related trials for Mandibular Asymmetry
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Mandibular Asymmetry, run by Konya Necmettin Erbakan Üniversitesi at 1 site in Turkey (Türkiye).
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 2 Oct 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Turkey (Türkiye). Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of Looksmaxxing AI in Detecting Chin Deviation (time frame: At study completion (October 2025)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 2 Oct 2025.