Gender differences in maxillary and mandibular morphology among the Jordanian population: Implications for orthodontic treatment and ai applications in dentistry

Gender differences in maxillary and mandibular morphology are important for orthodontics, surgery, and forensic identification. Cone-Beam Computed Tomography (CBCT) and Artificial Intelligence (AI) enhance diagnostic precision and efficiency, but AI adoption presents challenges such as data privacy and algorithmic bias. This study investigates gender-based differences in the morphometric features of the maxilla and mandible in Jordanian adults using Cone-Beam Computed Tomography (CBCT) and explores the potential of Artificial Intelligence (AI) in enhancing diagnostics and treatment planning. A retrospective study analyzed 100 CBCT images of Jordanian adults (20-45 years) from medical imaging centers (Sept 2023–Feb 2024). Carestream 3D software was used for image analysis by two researchers. Gender and lateralization differences were examined, along with jaw arch length and intercanine distance. Males exhibited significantly larger maxillary and mandibular dimensions compared to females, particularly in arch lengths and sinus dimensions (p < 0.05), and maxillary and mandibular arch lengths showed the greatest variations. Arch shape analysis revealed that round and U-shaped patterns were more common, with notable gender-specific variations. The findings confirm significant gender-related morphometric differences among Jordanians in jaw anatomy, supporting their relevance in orthodontic planning, forensic identification, and craniofacial analysis. Understanding these anatomical variations enhances personalized dental care. Integrating AI with CBCT imaging can improve landmark detection, treatment customization, and diagnostic precision, contributing to efficient, patient-centered dental interventions.