Looksmaxxing AI for Chin Deviation Detection

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.

Inclusion criteria

• 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

Exclusion criteria

• Photographs in which the patient's face appears slightly angled or turned sideways

Blurred or low-quality photographs with reduced clarity