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Artificial Intelligence in Rhinoplasty Recovery: Linguistic Intelligence and Machine Learning-Driven Insights.

Aynur Aliyeva^1,2, Elad Azizli³, Vusala Snyder⁴

¹Neuroscience Doctoral Program, Yeditepe University, Istanbul 34755, Turkey.

Journal of Clinical Medicine

|February 27, 2026

Summary

This summary is machine-generated.

ChatGPT-4 shows high accuracy and clarity for postoperative rhinoplasty questions, but patient-centered communication needs improvement. AI tools may assist, but cannot replace personalized medical advice or follow-up care.

Keywords:

ChatGPT-4 artificial intelligence linguistic analysis machine learning rhinoplasty

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Area of Science:

Medical Informatics
Artificial Intelligence in Medicine
Otolaryngology

Background:

Postoperative care is crucial for rhinoplasty outcomes.
Patients often seek readily accessible information regarding recovery.
Large language models (LLMs) like ChatGPT-4 offer potential for patient information dissemination.

Purpose of the Study:

To evaluate ChatGPT-4's performance as a postoperative information tool for rhinoplasty.
To assess the accuracy, clarity, relevance, and patient-centeredness of AI-generated responses.
To compare AI responses with expert otolaryngologist (ENT) evaluations.

Main Methods:

An observational, cross-sectional simulation study design was employed.
Ten standardized postoperative rhinoplasty questions were posed to ChatGPT-4.
Responses were independently rated by blinded ENT specialists using a structured performance instrument and linguistic/statistical analyses.

Main Results:

ChatGPT-4 achieved high accuracy (90%) and clarity (87%) scores.
Patient-centered communication scores were lower (77%).
Machine learning analysis identified clarity, diagnostic depth, and empathy as key factors for high ratings.

Conclusions:

ChatGPT-4 demonstrates significant potential in providing accurate and clear postoperative rhinoplasty information.
While AI tools can complement clinician counseling, they do not substitute for individualized medical advice or surgical follow-up.
Further development is needed to enhance the patient-centered communication capabilities of AI in medical contexts.