News Release

AI outperforms expert plastic surgeon in rhinoplasty consultations

Peer-Reviewed Publication

Mary Ann Liebert, Inc./Genetic Engineering News

Facial Plastic Surgery & Aesthetic Medicine

image: 

 

 Journal with the key mission of providing physicians with the most accurate and innovative information in the discipline of reconstructive and cosmetic facial plastic interventions.

view more 

Credit: Mary Ann Liebert Inc., publishers

In a new study, artificial intelligence in the form of ChatGPT outperformed an expert rhinoplasty surgeon in answering preoperative and postoperative patient questions related to nasal surgery. ChatGPT earned significantly higher ratings in accuracy, completeness, and overall quality, according to the study published in Facial Plastic Surgery & Aesthetic Medicine. Click here to read the article now.

Kay Durairaj, MD, and Omer Baker, from Pasadena, California , Dario Bertossi, MD, from University of Verona, Steven Dayan, MD, from University of Illinois, Chicago, Kian Karimi, MD, from Los Angeles California, Roy Kim, MD, from San Francisco, California, Sam Most, MD, from Stanford University, Enrico Robotti, MD,  from Bergamo Italy, and Frand Rosengaus, MD, from Mexico City, reported that ChatGPT was overwhelmingly preferred over physician responses, with evaluators favoring ChatGPT in 80.95% of instances. Their findings are presented in the article titled “Artificial Intelligence Versus Expert Plastic Surgeon: Comparative Study Shows ChatGPT ‘Wins’ Rhinoplasty Consultations: Should We Be Worried?”

“Our findings showed that ChatGPT displayed a remarkable ability to effectively respond to a wide breadth of patient questions, encompassing optics such as nonsurgical treatment options and postoperative care instructions,” stated the investigators. “In the majority of instances, ChatGPT performed at or above the level of an expert rhinoplasty surgeon.”

Facial Plastic Surgery & Aesthetic Medicine Editor-in-Chief Travis T. Tollefson, MD, MPH, University of California, Davis, states: “Online tools such as ChatGPT are making Artificial Intelligence (AI) or large language models (LLM) accessible to the public with so much excitement. To best serve our patients and the overall medical community, we must remain conscientious to the appropriate use of these technologies. It is astounding to read AI-generated content that has been edited in the writing style of Hemingway or Dostoevsky. It remains our responsibility to counsel patients on the occasional inaccurate statements made in AI-generated content. We can both acknowledge that most of our patients will be using AI and focus our efforts on maintaining the integrity of our patient education and consultation practices.”

About the Journal
Facial Plastic Surgery & Aesthetic Medicine is a multispecialty peer-reviewed journal with the key mission of providing physicians with the most accurate and innovative information in the discipline of reconstructive and cosmetic facial plastic interventions. Led by Editor-in-Chief Travis T. Tollefson, MD, MPH, University of California, Davis, the Journal publishes significant peer-reviewed articles on all aspects of reconstructive and cosmetic surgery of the head and neck. Facial Plastic Surgery & Aesthetic Medicine is the official publication of the American Academy of Facial Plastic and Reconstructive Surgery, Inc., the European Academy of Facial Plastic Surgery, and the International Federation of Facial Plastic Surgery Societies. For more information and a sample issue, please visit the Facial Plastic Surgery & Aesthetic Medicine website.

About the Publisher
Mary Ann Liebert, Inc. is a global media company dedicated to creating, curating, and delivering impactful peer-reviewed research and authoritative content services to advance the fields of biotechnology and the life sciences, specialized clinical medicine, and public health and policy. For complete information, please visit the Mary Ann Liebert, Inc. website.


Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.