The Future of Personalized Rhinoplasty: Integrating AI with Genomics and Facial Typing

Abstract

Rhinoplasty remains one of the most complex procedures in aesthetic surgery. Traditional standardized approaches often fail to capture the diversity of individual anatomy and cultural expectations. This review evaluates the role of artificial intelligence (AI), facial typing, and genomics in advancing personalized rhinoplasty. We systematically searched PubMed, Scopus, and Google Scholar in July 2025 using terms related to rhinoplasty, AI, facial typing, and genomics. We included studies addressing AI-driven planning or simulations, morphometric analysis, and genetic influences on nasal shape or wound healing. Two reviewers independently screened and extracted data. Because of study heterogeneity, we synthesized findings narratively. Five studies met inclusion criteria, including two narrative reviews, two cross-sectional analyses, and one experimental study. AI-based simulations improved planning accuracy and aligned patient expectations with surgical outcomes. Facial typing studies emphasized the need for culturally inclusive morphometric models. Genomic research identified genetic markers linked to nasal shape and wound healing, suggesting potential for biologically tailored interventions. AI, facial typing, and genomics are actively transforming rhinoplasty into a personalized discipline. To realize this potential, surgeons must expand diverse datasets, validate genomic insights, and communicate outcomes responsibly, ensuring that technology enhances safety, equity, and patient satisfaction.