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Healthc Inform Res > Volume 15(2); 2009 > Article
Journal of Korean Society of Medical Informatics 2009;15(2):175-189.
DOI: https://doi.org/10.4258/jksmi.2009.15.2.175    Published online June 30, 2009.
Basic Concepts and Principles of Data Mining in Clinical Practice
Sun Mi Lee1, Rae Woong Park2,3
1The Catholic University of Korea College of Nursing, Korea.
2Department of Biomedical Informatics, School of Medicine, Ajou University, Korea.
3Institute for u-health Information Research, Ajou University Medical Center, Korea.
Correspondence:  Rae Woong Park,
Received: 15 June 2009

Recently, many hospitals have been adopting clinical data warehouses (CDW) as well as electronic medical records. These new hospital information systems are inevitably introducing very large amounts of clinical data that might be useful for further analysis. However, the electronic clinical data in the CDW are usually byproducts of clinical practice rather than the product of research. Therefore, they include inconsistent and sometimes erroneous information that might not have the specific context of the clinical situations. Data miners usually have various academic backgrounds such as electronics, informatics, statistics, biomedicine, and public health. If the complex situations surrounding the clinical data are not well understood, investigators performing data mining in clinical fields may have problems assessing the information they are confronted with. Here, we would like to introduce some basic concepts on the principles of data mining in clinical fields including legal and ethical considerations as well as technical concerns.

Key Words: Clinical Data Mining, Machine Learning
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