Mapping Phenotypic Information in Heterogeneous Textual Sources to a Domain-Specific Terminological Resource

Author:

Alnazzawi NohaORCID,Thompson Paul,Ananiadou Sophia

Funder

Medical Research Council

Defense Advanced Research Projects Agency

Engineering and Physical Sciences Research Council

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference91 articles.

1. Richesson R, Smerek M. Electronic health records-based phenotyping. Rethinking Clinical Trials: A Living Textbook of Pragmatic Clinical Trials 2015. Available at: https://sites.duke.edu/rethinkingclinicaltrials/ehr-phenotyping/. Accessed 12th August 2016.

2. Patrick J, Wang Y, Budd P. Automatic Mapping Clinical Notes to Medical Terminologies. In: Proceedings of the 2006 Australasian Language Technology Workshop; 2006. p. 75–82.

3. Patrick J, Wang Y, Budd P. An automated system for conversion of clinical notes into SNOMED clinical terminology. In: Proceedings of the Fifth Australasian symposium on ACSW frontiers; 2007. p. 219–26.

4. Using text mining techniques to extract phenotypic information from the PhenoCHF corpus;N Alnazzawi;BMC medical informatics and decision making,2015

5. Recognizing obesity and comorbidities in sparse data;Ö Uzuner;Journal of the American Medical Informatics Association,2009

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