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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...
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| Pubblicato in: | Int J Data Sci Anal |
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| Autori principali: | , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Springer International Publishing
2016
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5479362/ https://ncbi.nlm.nih.gov/pubmed/28691055 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s41060-016-0034-x |
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