Your browser doesn't support javascript.
loading
Capacity for large language model chatbots to aid in orthopedic management, research, and patient queries.
Sosa, Branden R; Cung, Michelle; Suhardi, Vincentius J; Morse, Kyle; Thomson, Andrew; Yang, He S; Iyer, Sravisht; Greenblatt, Matthew B.
Afiliação
  • Sosa BR; Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, New York, USA.
  • Cung M; Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, New York, USA.
  • Suhardi VJ; Research Division and Department of Orthopedic Surgery, Hospital for Special Surgery, New York, New York, USA.
  • Morse K; Department of Spine Surgery, Hospital for Special Surgery, New York, New York, USA.
  • Thomson A; Research Division and Department of Orthopedic Surgery, Hospital for Special Surgery, New York, New York, USA.
  • Yang HS; Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, New York, USA.
  • Iyer S; Department of Spine Surgery, Hospital for Special Surgery, New York, New York, USA.
  • Greenblatt MB; Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, New York, USA.
J Orthop Res ; 42(6): 1276-1282, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38245845
ABSTRACT
Large language model (LLM) chatbots possess a remarkable capacity to synthesize complex information into concise, digestible summaries across a wide range of orthopedic subject matter. As LLM chatbots become widely available they will serve as a powerful, accessible resource that patients, clinicians, and researchers may reference to obtain information about orthopedic science and clinical management. Here, we examined the performance of three well-known and easily accessible chatbots-ChatGPT, Bard, and Bing AI-in responding to inquiries relating to clinical management and orthopedic concepts. Although all three chatbots were found to be capable of generating relevant responses, ChatGPT outperformed Bard and BingAI in each category due to its ability to provide accurate and complete responses to orthopedic queries. Despite their promising applications in clinical management, shortcomings observed included incomplete responses, lack of context, and outdated information. Nonetheless, the ability for these LLM chatbots to address these inquires has largely yet to be evaluated and will be critical for understanding the risks and opportunities of LLM chatbots in orthopedics.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ortopedia Limite: Humans Idioma: En Revista: J Orthop Res Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ortopedia Limite: Humans Idioma: En Revista: J Orthop Res Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos