Mining the electronic health record for disease knowledge.
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 natural language processing, standards, and data privacy and security are also discussed in the context of this framework.
Center for Clinical and Translational Science, University of Vermont, Burlington, VT, USA, liz.chen@uvm.edu.
Elizabeth S
ES
Chen
Indra Neil
IN
Sarkar
D057225:Data Mining / Q000379:methods*; D057286:Electronic Health Records; D006801:Humans; D051188:Knowledge Bases; D009323:Natural Language Processing