GPT-4 accuracy and completeness against International Consensus Statement on Allergy and Rhinology: Rhinosinusitis.

Yoshiyasu, Yuki; Wu, Franklin; Dhanda, Aatin K; Gorelik, Daniel; Takashima, Masayoshi; Ahmed, Omar G

Yoshiyasu, Yuki; Wu, Franklin; Dhanda, Aatin K; Gorelik, Daniel; Takashima, Masayoshi; Ahmed, Omar G.

Afiliación

Yoshiyasu Y; Department of Otolaryngology-Head and Neck Surgery, University of Texas Medical Branch, Galveston, Texas, USA.
Wu F; Department of Otolaryngology-Head and Neck Surgery, Houston Methodist Hospital, Houston, Texas, USA.
Dhanda AK; Department of Otolaryngology-Head and Neck Surgery, Houston Methodist Hospital, Houston, Texas, USA.
Gorelik D; Department of Otolaryngology-Head and Neck Surgery, Houston Methodist Hospital, Houston, Texas, USA.
Takashima M; Department of Otolaryngology-Head and Neck Surgery, Houston Methodist Hospital, Houston, Texas, USA.
Ahmed OG; Department of Otolaryngology-Head and Neck Surgery, Houston Methodist Hospital, Houston, Texas, USA.

Int Forum Allergy Rhinol ; 13(12): 2231-2234, 2023 Dec.

Article en En | MEDLINE | ID: mdl-37260081

Asunto(s)

Hipersensibilidad; Rinitis; Sinusitis; Humanos; Rinitis/diagnóstico; Rinitis/terapia; Sinusitis/diagnóstico; Sinusitis/terapia; Consenso; Enfermedad Crónica

Palabras clave

Large language model (LLM); chronic rhinosinusitis; rhinosinusitis; sinusitis

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Sinusitis / Rinitis / Hipersensibilidad Límite: Humans Idioma: En Revista: Int Forum Allergy Rhinol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

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