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Handling hybrid and missing data in constraint-based causal discovery to study the etiology of ADHD
Causal discovery is an increasingly important method for data analysis in the field of medical research. In this paper, we consider two challenges in causal discovery that occur very often when working with medical data: a mixture of discrete and continuous variables and a substantial amount of miss...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5479362/ https://www.ncbi.nlm.nih.gov/pubmed/28691055 http://dx.doi.org/10.1007/s41060-016-0034-x |