Examining the Use of an Artificial Intelligence Model to Diagnose Influenza: Development and Validation Study.

Okiyama, Sho; Fukuda, Memori; Sode, Masashi; Takahashi, Wataru; Ikeda, Masahiro; Kato, Hiroaki; Tsugawa, Yusuke; Iwagami, Masao

Okiyama, Sho; Fukuda, Memori; Sode, Masashi; Takahashi, Wataru; Ikeda, Masahiro; Kato, Hiroaki; Tsugawa, Yusuke; Iwagami, Masao.

Afiliación

Okiyama S; Aillis, Inc, Tokyo, Japan.
Fukuda M; Japanese Red Cross Medical Center, Tokyo, Japan.
Sode M; Aillis, Inc, Tokyo, Japan.
Takahashi W; Department of Health Informatics, Graduate School of Medicine, School of Public Health, Kyoto University, Kyoto, Japan.
Ikeda M; Aillis, Inc, Tokyo, Japan.
Kato H; Aillis, Inc, Tokyo, Japan.
Tsugawa Y; Aillis, Inc, Tokyo, Japan.
Iwagami M; Department of Palliative Therapy, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan.

J Med Internet Res ; 24(12): e38751, 2022 12 23.

Article en En | MEDLINE | ID: mdl-36374004

Asunto(s)

Aprendizaje Profundo; Gripe Humana; Humanos; Inteligencia Artificial; Gripe Humana/diagnóstico; Curva ROC; Sensibilidad y Especificidad; Estudios Retrospectivos

Palabras clave

deep learning; diagnostic prediction; influenza; pharynx; physical examination

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Gripe Humana / Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: J Med Internet Res Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Japón

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