- Title Information
- Title
- Mining the electronic health record for disease knowledge
- Name:
Personal
- Name Part
- Chen, Elizabeth S.
- Role
- Role Term:
Text (marcrelator)
- author
- Name:
Personal
- Name Part
- Sarkar, Indra Neil
- Role
- Role Term:
Text (marcrelator)
- author
- Type of Resource
- text
- Genre (Local)
- chapters
- Origin Information
- Date Created
(keyDate="yes", encoding="w3cdtf")
- 2014
- Language
- Language Term:
Code (ISO639-2B)
- eng
- Note
(displayLabel="Source")
- Electronic Health Record
- Note
(displayLabel="Method")
- Data Mining
- 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.
- Note:
funding
- This research was supported in part by the National Library of Medicine of the National Institutes of Health under award number R01LM011364
- Note
- Chapter from Methods in Molecular Biology
- Related Item:
Host
(displayLabel="Published in")
- Title Information
- Title
- Methods of Molecular Biology
- partName
- 1159
- Origin Information
- Date Created
- 2014
- Date Created
(keyDate="yes", encoding="w3cdtf")
- 2014
- Physical Description
- Extent
- p. 29-286
- Identifier:
PubMed ID
- PMID: 24788272
- Identifier:
DOI
- doi: 10.1007/978-1-4939-0709-0_15
- Access Condition:
use and reproduction
(href="https://creativecommons.org/licenses/by-nc/4.0/")
- This work is licensed under a
Creative Commons Attribution-NonCommercial 4.0 International License
- Access Condition:
logo
(href="https://i.creativecommons.org/l/by-nc/4.0/88x31.png")