N-gram support vector machines for scalable procedure and diagnosis classification, with applications to clinical free text data from the intensive care unit

BACKGROUND: Existing risk adjustment models for intensive care unit (ICU) outcomes rely on manual abstraction of patient-level predictors from medical charts. Developing an automated method for abstracting these data from free text might reduce cost and data collection times. OBJECTIVE: To develop a...

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Détails bibliographiques
Auteurs principaux: Marafino, Ben J, Davies, Jason M, Bardach, Naomi S, Dean, Mitzi L, Dudley, R Adams
Format: Artigo
Langue:Inglês
Publié: BMJ Publishing Group 2014
Sujets:
Focus on Biomedical Natural Language Processing and Data Modeling
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC4147615/
https://ncbi.nlm.nih.gov/pubmed/24786209
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1136/amiajnl-2014-002694
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