Applying MetaMap to Medline for identifying novel associations in a large clinical dataset: a feasibility analysis

@article{Hanauer2014ApplyingMT,
  title={Applying MetaMap to Medline for identifying novel associations in a large clinical dataset: a feasibility analysis},
  author={David A. Hanauer and Mohammed Saeed and Kai Zheng and Qiaozhu Mei and Kerby Shedden and Alan R. Aronson and Naren Ramakrishnan},
  journal={Journal of the American Medical Informatics Association : JAMIA},
  year={2014},
  volume={21 5},
  pages={925-37}
}
OBJECTIVE We describe experiments designed to determine the feasibility of distinguishing known from novel associations based on a clinical dataset comprised of International Classification of Disease, V.9 (ICD-9) codes from 1.6 million patients by comparing them to associations of ICD-9 codes derived from 20.5 million Medline citations processed using MetaMap. Associations appearing only in the clinical dataset, but not in Medline citations, are potentially novel. METHODS Pairwise… CONTINUE READING
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