Artificial Intelligence for Patient Support: Assessing Retrieval-Augmented Generation for Answering Postoperative Rhinoplasty Questions.

Journal: Aesthetic surgery journal
Published Date:

Abstract

BACKGROUND: Although artificial intelligence (AI) is revolutionizing healthcare, inaccurate or incomplete information from pretrained large language models (LLMs) like ChatGPT poses significant risks to patient safety. Retrieval-augmented generation (RAG) offers a promising solution by leveraging curated knowledge bases to enhance accuracy and reliability, especially in high-demand specialties like plastic surgery.

Authors

  • Ariana Genovese
  • Srinivasagam Prabha
  • Sahar Borna
    Division of Plastic Surgery, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL, 32224, USA.
  • Cesar A Gomez-Cabello
    Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.
  • Syed Ali Haider
    Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.
  • Maissa Trabilsy
  • Cui Tao
    The University of Texas Health Science Center at Houston, USA.
  • Keith T Aziz
  • Peter M Murray
  • Antonio Jorge Forte
    Division of Plastic Surgery, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL, 32224, USA. ajvforte@yahoo.com.br.