Machine Learning and Improved Quality Metrics in Acute Intracranial Hemorrhage by Noncontrast Computed Tomography.

Davis, Melissa A; Rao, Balaji; Cedeno, Paul A; Saha, Atin; Zohrabian, Vahe M

Davis, Melissa A; Rao, Balaji; Cedeno, Paul A; Saha, Atin; Zohrabian, Vahe M.

Afiliación

Davis MA; Department of Radiology and Biomedical Imaging ,Yale School of Medicine, Yale University, New Haven, CT 06520.
Rao B; Department of Radiology and Biomedical Imaging ,Yale School of Medicine, Yale University, New Haven, CT 06520.
Cedeno PA; Department of Radiology and Biomedical Imaging ,Yale School of Medicine, Yale University, New Haven, CT 06520.
Saha A; Department of Radiology and Biomedical Imaging ,Yale School of Medicine, Yale University, New Haven, CT 06520.
Zohrabian VM; Department of Radiology and Biomedical Imaging ,Yale School of Medicine, Yale University, New Haven, CT 06520.. Electronic address: vahe.zohrabian@gmail.com.

Curr Probl Diagn Radiol ; 51(4): 556-561, 2022.

Article en En | MEDLINE | ID: mdl-33243455

Asunto(s)

Inteligencia Artificial; Benchmarking; Servicio de Urgencia en Hospital; Humanos; Hemorragias Intracraneales/diagnóstico por imagen; Aprendizaje Automático; Estudios Retrospectivos; Tomografía Computarizada por Rayos X/métodos

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Benchmarking Tipo de estudio: Observational_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Curr Probl Diagn Radiol Año: 2022 Tipo del documento: Article

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