Review Maps AI Uses in Rhinoplasty

A systematic review by Mitra Montazerlotf and Nima Dehghani, published in the Journal of Craniomaxillofacial Research in 2026, examined how artificial intelligence is being used across rhinoplasty care. The authors searched PubMed/MEDLINE, Scopus, Web of Science and Google Scholar for studies published between 2015 and 2026; 39 studies met the inclusion criteria.

The reviewed applications covered five areas: preoperative planning and simulation; aesthetic analysis and attractiveness measurement; patient counseling with large language models; intraoperative guidance using augmented reality; and postoperative outcome evaluation. Reported model accuracies ranged from 82% to 97%. In structured counseling evaluations, large language models performed comparably to or better than expert surgeons.

The authors said algorithmic bias, limited diversity in datasets, a lack of prospective validation and unresolved ethical concerns currently limit widespread clinical adoption. They concluded that AI may improve precision and reproducibility in rhinoplasty, but should support rather than replace surgical expertise.

A systematic review by Mitra Montazerlotf and Nima Dehghani, published in the Journal of Craniomaxillofacial Research in 2026, examined how artificial intelligence is being used across rhinoplasty care. The authors searched PubMed/MEDLINE, Scopus, Web of Science and Google Scholar for studies published between 2015 and 2026; 39 studies met the inclusion criteria.

The reviewed applications covered five areas: preoperative planning and simulation; aesthetic analysis and attractiveness measurement; patient counseling with large language models; intraoperative guidance using augmented reality; and postoperative outcome evaluation. Reported model accuracies ranged from 82% to 97%. In structured counseling evaluations, large language models performed comparably to or better than expert surgeons.

The authors said algorithmic bias, limited diversity in datasets, a lack of prospective validation and unresolved ethical concerns currently limit widespread clinical adoption. They concluded that AI may improve precision and reproducibility in rhinoplasty, but should support rather than replace surgical expertise.