Cargando…
Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences
Machine learning (ML) methodology used in the social and health sciences needs to fit the intended research purposes of description, prediction, or causal inference. This paper provides a comprehensive, systematic meta-mapping of research questions in the social and health sciences to appropriate ML...
Autores principales: | Leist, Anja K., Klee, Matthias, Kim, Jung Hyun, Rehkopf, David H., Bordas, Stéphane P. A., Muniz-Terrera, Graciela, Wade, Sara |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9581488/ https://www.ncbi.nlm.nih.gov/pubmed/36260666 http://dx.doi.org/10.1126/sciadv.abk1942 |
Ejemplares similares
-
How to make causal inferences using texts
por: Egami, Naoki, et al.
Publicado: (2022) -
A large-scale observational study of the causal effects of a behavioral health nudge
por: Nazaret, Achille, et al.
Publicado: (2023) -
Pathways for diversifying and enhancing science advocacy
por: Tormos-Aponte, Fernando, et al.
Publicado: (2023) -
Systematic inference identifies a major source of heterogeneity in cell signaling dynamics: The rate-limiting step number
por: Kim, Dae Wook, et al.
Publicado: (2022) -
Metabolomics in archaeological science: A review of their advances and present requirements
por: Badillo-Sanchez, Diego, et al.
Publicado: (2023)