Linear methods for optimization and prediction in healthcare : make causal inferences in health data using R and Python /

"Linear methods have traditionally been the workhorse of data analysis in many domains, and health-related applications are no exception. However, linear methods have a lot more to offer than standard regression analysis. This video explains why linear thinking remains a powerful and sophistica...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Formato: Electrónico Video
Idioma:Inglés
Publicado: [Place of publication not identified] : O'Reilly Media, [2017]
Temas:
Medical care > Data processing.
Quantitative research.
Linear models (Statistics)
Data mining.
Data Mining
Recherche quantitative.
Exploration de données (Informatique)
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Nielsen, Aileen,  |e on-screen presenter. 
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520 |a "Linear methods have traditionally been the workhorse of data analysis in many domains, and health-related applications are no exception. However, linear methods have a lot more to offer than standard regression analysis. This video explains why linear thinking remains a powerful and sophisticated way to think about data for prediction, causal analysis, and optimization in health tech. Designed for data scientists and for data savvy health care managers and clinicians, it demonstrates how to strengthen the conclusions you draw from health-related data and how to better allocate your health care resources."--Resource description page 
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