Ontological Models Supporting Covariates Selection in Observational Studies.
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.
Palabras clave
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