Your browser doesn't support javascript.
loading
Accuracy and Bias in Artificial Intelligence Chatbot Recommendations for Oculoplastic Surgeons.
Parikh, Alomi O; Oca, Michael C; Conger, Jordan R; McCoy, Allison; Chang, Jessica; Zhang-Nunes, Sandy.
Afiliación
  • Parikh AO; Ophthalmology, USC Roski Eye Institute, Keck School of Medicine, University of Southern California, Los Angeles, USA.
  • Oca MC; Ophthalmology, University of California San Diego School of Medicine, La Jolla, USA.
  • Conger JR; Oculofacial Plastic Surgery, USC Roski Eye Institute, Keck School of Medicine, University of Southern California, Los Angeles, USA.
  • McCoy A; Oculofacial Plastic Surgery, Del Mar Plastic Surgery, San Diego, USA.
  • Chang J; Oculofacial Plastic Surgery, USC Roski Eye Institute, Keck School Medicine, University of Southern California, Los Angeles, USA.
  • Zhang-Nunes S; Ophthalmology, USC Roski Eye Institute, Keck School Medicine, University of Southern California, Los Angeles, USA.
Cureus ; 16(4): e57611, 2024 Apr.
Article en En | MEDLINE | ID: mdl-38707042
ABSTRACT
Purpose The purpose of this study is to assess the accuracy of and bias in recommendations for oculoplastic surgeons from three artificial intelligence (AI) chatbot systems. Methods ChatGPT, Microsoft Bing Balanced, and Google Bard were asked for recommendations for oculoplastic surgeons practicing in 20 cities with the highest population in the United States. Three prompts were used "can you help me find (an oculoplastic surgeon)/(a doctor who does eyelid lifts)/(an oculofacial plastic surgeon) in (city)." Results A total of 672 suggestions were made between (oculoplastic surgeon; doctor who does eyelid lifts; oculofacial plastic surgeon); 19.8% suggestions were excluded, leaving 539 suggested physicians. Of these, 64.1% were oculoplastics specialists (of which 70.1% were American Society of Ophthalmic Plastic and Reconstructive Surgery (ASOPRS) members); 16.1% were general plastic surgery trained, 9.0% were ENT trained, 8.8% were ophthalmology but not oculoplastics trained, and 1.9% were trained in another specialty. 27.7% of recommendations across all AI systems were female. Conclusions Among the chatbot systems tested, there were high rates of inaccuracy up to 38% of recommended surgeons were nonexistent or not practicing in the city requested, and 35.9% of those recommended as oculoplastic/oculofacial plastic surgeons were not oculoplastics specialists. Choice of prompt affected the result, with requests for "a doctor who does eyelid lifts" resulting in more plastic surgeons and ENTs and fewer oculoplastic surgeons. It is important to identify inaccuracies and biases in recommendations provided by AI systems as more patients may start using them to choose a surgeon.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Cureus Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Cureus Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos