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What are the potential benefits of using data mining in health care?
Review the information in the Learning Resources on the different types of data warehousing and how the one selected impacts data mining.
Review the Hey article, “The Next Scientific Revolution.” Consider how data mining through machine learning can be applied to health care.
Read the section on data mining on pp. 671-673 in the course text, Database Systems: Design, Implementation, and Management and consider how it connects to the content in the Hey article. According to the text, are the data mining techniques Hey describes guided or automated?
Using the Walden Library, locate at least one specific example of each type of data mining (guided and automated) in health care. The examples you identify should be different from the examples discussed in the Hey article.
Reflect on your initial impressions of automated data mining in health care. What are your thoughts on applying this type of data mining to patient care? Consider possible drawbacks of both guided and automated data mining. What approaches and strategies could be used to address those concerns?
Consider any ethical ramifications of using data mining or machine learning as a tool for prognosis.
BY DAY 3
Post an analysis of how data mining can be beneficial to a health care system. Assess how the type of data warehousing used can impact the ability to mine data. Describe examples of the successful use of guided data mining and automated data mining within health care and cite your source. Describe any reservations you have or ethical issues you foresee in using data mining to provide health care information. What approaches and strategies could be used to address those concerns? Justify your responses.
Use these references:
Coronel, C. & Morris, S. (2017). Database systems: Design, implementation, and management (12th ed.). Boston, MA: Cengage Learning.
Kristianson, K. J., Ljunggren, H., & Gustafsson, L. L. (2009). Data extraction from a semi-structured electronic medical record system for outpatients: A model to facilitate the access and use of data for quality control and research. Health Informatics Journal, 15(4), 305–319.
Kulkarni, M. (2010). A case-based data warehousing courseware. 2010 IEEE International Conference on Information Reuse and Integration (IRI), 245–248.
Jukic, N., & Nicholas, J. (2010). A framework for collecting and defining requirements for data warehousing projects. Journal of Computing & Information Technology, 18(4), 377–384.
Hey, T. (2010). The big idea: The next scientific revolution. Harvard Business Review, 88(11), 56–63.
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