Predicting facility-based delivery in Zanzibar: The vulnerability of machine learning algorithms to adversarial attacks.

Tsai, Yi-Ting; Fulcher, Isabel R; Li, Tracey; Sukums, Felix; Hedt-Gauthier, Bethany

Tsai, Yi-Ting; Fulcher, Isabel R; Li, Tracey; Sukums, Felix; Hedt-Gauthier, Bethany.

Afiliação

Tsai YT; Department of Biostatistics, Harvard Chan School of Public Health, Boston, USA.
Fulcher IR; Department of Global Health and Social Medicine, Harvard Medical School, Boston, USA.
Li T; Harvard Data Science Initiative, Harvard University, Cambridge, USA.
Sukums F; D-tree International, Zanzibar, Tanzania.
Hedt-Gauthier B; Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania.

Heliyon ; 9(5): e16244, 2023 May.

Article em En | MEDLINE | ID: mdl-37234636

Palavras-chave

Adversarial attack; Community health worker intervention; Digital health; Facility delivery; Machine learning; Maternal health

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Heliyon Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

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