Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources

Objective Analysis of narrative (text) data from electronic health records (EHRs) can improve population-scale phenotyping for clinical and genetic research. Currently, selection of text features for phenotyping algorithms is slow and laborious, requiring extensive and iterative involvement by domai...

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Dades bibliogràfiques
Publicat a:J Am Med Inform Assoc
Autors principals: Yu, Sheng, Liao, Katherine P, Shaw, Stanley Y, Gainer, Vivian S, Churchill, Susanne E, Szolovits, Peter, Murphy, Shawn N, Kohane, Isaac S., Cai, Tianxi
Format: Artigo
Idioma:Inglês
Publicat: Oxford University Press 2015
Matèries:
Focus on Natural Language Processing
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC4986664/
https://ncbi.nlm.nih.gov/pubmed/25929596
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamia/ocv034
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