Computational Phenotype Discovery Using Unsupervised Feature Learning over Noisy, Sparse, and Irregular Clinical Data

Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task...

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Detalles Bibliográficos
Autores principales: Lasko, Thomas A., Denny, Joshua C., Levy, Mia A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691199/
https://www.ncbi.nlm.nih.gov/pubmed/23826094
http://dx.doi.org/10.1371/journal.pone.0066341

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691199/
https://www.ncbi.nlm.nih.gov/pubmed/23826094
http://dx.doi.org/10.1371/journal.pone.0066341

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