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Evaluating the Effectiveness of Artificial Intelligence-powered Large Language Models Application in Disseminating Appropriate and Readable Health Information in Urology.
Davis, Ryan; Eppler, Michael; Ayo-Ajibola, Oluwatobiloba; Loh-Doyle, Jeffrey C; Nabhani, Jamal; Samplaski, Mary; Gill, Inderbir; Cacciamani, Giovanni E.
Afiliación
  • Davis R; USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California.
  • Eppler M; AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California.
  • Ayo-Ajibola O; USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California.
  • Loh-Doyle JC; AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California.
  • Nabhani J; USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California.
  • Samplaski M; AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California.
  • Gill I; USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California.
  • Cacciamani GE; USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California.
J Urol ; 210(4): 688-694, 2023 10.
Article en En | MEDLINE | ID: mdl-37428117
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Urología / Alfabetización en Salud Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: J Urol Año: 2023 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Urología / Alfabetización en Salud Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: J Urol Año: 2023 Tipo del documento: Article