Description
- Abstract:
- The growing amount and availability of electronic health record (EHR) data present enhanced opportunities for discovering new knowledge about diseases. In the past decade, there has been an increasing number of data and text mining studies focused on the identification of disease associations (e.g., disease--disease, disease--drug, and disease--gene) in structured and unstructured EHR data. This chapter presents a knowledge discovery framework for mining the EHR for disease knowledge and describes each step for data selection, preprocessing, transformation, data mining, and interpretation/validation. Topics including national language processing, standards, and data privacy and security are also discussed in the context of this framework.
- Notes:
- Source: Electronic Health Record
- Method: Data Mining
- This research was supported in part by the National Library of Medicine of the National Institutes of Health under award number R01LM011364
- Chapter from Methods in Molecular Biology
Access Conditions
- Use and Reproduction
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- This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Citation
Chen, Elizabeth S., and Sarkar, Indra Neil,
"Mining the electronic health record for disease knowledge"
(2014).
SFHERE Publications and Presentations.
Brown Digital Repository. Brown University Library.
https://repository.library.brown.edu/studio/item/bdr:697500/
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Collection:
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SFHERE Publications and Presentations
This collection houses journal articles, conference papers and presentations, and abstracts and posters authored by members of the SFHERE team....