Artificial Intelligence Versus Expert Plastic Surgeon: Comparative Study Shows ChatGPT "Wins" Rhinoplasty Consultations: Should We Be Worried?
K Kay DurairajOmer BakerDario BertossiSteven DayanKian KarimiRoy KimSam P MostEnrico RobottiFrank RosengausPublished in: Facial plastic surgery & aesthetic medicine (2023)
Introduction: Large language models, such as ChatGPT, hold tremendous promise to bridge gaps in patient education and enhance the decision-making resources available online for patients seeking nasal surgery. Objective: To compare the performance of ChatGPT in answering preoperative and postoperative patient questions related to septorhinoplasty. Methods: Two sets of responses were collected for the questions: one from an expert rhinoplasty surgeon with over two decades of experience, and the other from ChatGPT-3.5. Seven expert rhinoplasty surgeons, blinded to the source of responses, independently assessed the responses using a 5-point Likert scale in four performance areas: empathy, accuracy, completeness, and overall quality. Results: ChatGPT outperformed physician responses in three of the four performance areas, earning significantly higher ratings in accuracy, completeness, and overall quality ( p < 0.001). In addition, ChatGPT was overwhelmingly preferred over physician responses ( p < 0.001), with evaluators favoring ChatGPT in 80.95% of instances. Conclusions: ChatGPT has demonstrated its remarkable ability to deliver accurate, complete, and high-quality responses to preoperative and postoperative patient questions. Although certain improvements are warranted, this artificial intelligence tool has shown its potential to effectively counsel and educate prospective septorhinoplasty patients at a level comparable with or exceeding that of an expert surgeon.
Keyphrases
- artificial intelligence
- big data
- machine learning
- deep learning
- emergency department
- clinical practice
- primary care
- end stage renal disease
- healthcare
- quality improvement
- minimally invasive
- chronic kidney disease
- robot assisted
- clinical trial
- ejection fraction
- high resolution
- atrial fibrillation
- patient reported outcomes
- study protocol
- percutaneous coronary intervention
- health information
- patient reported