CT nasal and sinus metrics with machine learning for sex prediction in Egyptians

ML analysis of CT-based nasal and maxillary sinus measurements achieved AUC 0.771 and 74.4% accuracy for sex prediction in 195 Egyptians. Nasofrontal angle and nasion-tip distance were top predictors.

• Cross-sectional study of 195 adult Egyptians (100 female, 95 male) using paranasal sinus CT.
• Best ML model AUC 0.771; highest accuracy 74.4% for sex classification.
• Nasofrontal angle, nasion-tip distance, and mean anteroposterior maxillary dimension were most predictive measurements.

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