Developing Machine Learning and Statistical Tools to Evaluate the Accessibility of Public Health Advice on Infectious Diseases among Vulnerable People.

Xie, Wenxiu; Ji, Meng; Zhao, Mengdan; Lam, Kam-Yiu; Chow, Chi-Yin; Hao, Tianyong

Xie, Wenxiu; Ji, Meng; Zhao, Mengdan; Lam, Kam-Yiu; Chow, Chi-Yin; Hao, Tianyong.

Afiliação

Xie W; Department of Computer Science, City University of Hong Kong, Hong Kong, China.
Ji M; School of Languages and Cultures, University of Sydney, Sydney, Australia.
Zhao M; School of Languages and Cultures, University of Sydney, Sydney, Australia.
Lam KY; Department of Computer Science, City University of Hong Kong, Hong Kong, China.
Chow CY; Department of Computer Science, City University of Hong Kong, Hong Kong, China.
Hao T; School of Computer Science, South China Normal University, Guangzhou, China.

Comput Intell Neurosci ; 2021: 1916690, 2021.

Article em En | MEDLINE | ID: mdl-34925484

Assuntos

COVID-19; Doenças Transmissíveis; Infecção por Zika virus; Zika virus; Teorema de Bayes; Doenças Transmissíveis/epidemiologia; Humanos; Aprendizado de Máquina; Pandemias; Saúde Pública; SARS-CoV-2

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Transmissíveis / Zika virus / Infecção por Zika virus / COVID-19 Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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