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Ontological Models Supporting Covariates Selection in Observational Studies.
Pressat Laffouilhère, Thibaut; Grosjean, Julien; Bénichou, Jacques; Darmoni, Stefan J; Soualmia, Lina F.
Afiliación
  • Pressat Laffouilhère T; CHU Rouen, Department of Biomedical Informatics, F-76000 Rouen, France.
  • Grosjean J; CHU Rouen, Department of Biostatistics, F-76000 Rouen, France.
  • Bénichou J; Normandie Univ, UNIROUEN, LITIS EA 4108, F-76000 Rouen, France.
  • Darmoni SJ; CHU Rouen, Department of Biomedical Informatics, F-76000 Rouen, France.
  • Soualmia LF; LIMICS U1142, Sorbonne Université, Paris, France.
Stud Health Technol Inform ; 281: 1095-1096, 2021 May 27.
Article en En | MEDLINE | ID: mdl-34042854
ABSTRACT
In the context of causal inference, biostatisticians use causal diagrams to select covariates in order to build multivariate models. These diagrams represent datasets variables and their relations but have some limitations (representing interactions, bidirectional causal relations). The MetBrAYN project aims at building an ontological-based process to tackle these issues. The knowledge acquired by the biostatistician during a methodological consultation for a research question will be represented in a general ontology. In order to aggregate various forms of knowledge the ontology will act as a wrapper. Ontology-based causal diagrams will be semi-automatically built. Founded on inference rules, the global system will help biostatisticians to curate it and to visualize recommended covariates for their research question.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Causalidad Tipo de estudio: Observational_studies / Prognostic_studies Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2021 Tipo del documento: Article País de afiliación: Francia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Causalidad Tipo de estudio: Observational_studies / Prognostic_studies Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2021 Tipo del documento: Article País de afiliación: Francia