A Comparative Analysis of Data Mining Techniques Using Health Care Data
Location
CSU 253/254/255
Start Date
13-4-2004 12:45 PM
End Date
13-4-2004 2:45 PM
Student's Major
Computer Information Science
Student's College
Science, Engineering and Technology
Mentor's Name
Sarah Klammer
Mentor's Department
Computer Information Science
Mentor's College
Science, Engineering and Technology
Description
The Open Door Health Center is a clinic that provides health care services to the underserved in south central Minnesota. This includes uninsured and underinsured people primarily in Region 9. These patients may have unique health care needs that have not been identified in the past. Data mining is useful for identification of hidden trends in data and has been used to evaluate data that have been collected about the patients seen at the clinic. This research project has explored and compared the results of two data mining techniques, using patient demographics and social history for the standard data set. The techniques that will be discussed included Supervised Learning and Unsupervised Clustering as used to search for hidden trends in the data set. The knowledge gained from the data mining session is given as a model or generalization of the data.
A Comparative Analysis of Data Mining Techniques Using Health Care Data
CSU 253/254/255
The Open Door Health Center is a clinic that provides health care services to the underserved in south central Minnesota. This includes uninsured and underinsured people primarily in Region 9. These patients may have unique health care needs that have not been identified in the past. Data mining is useful for identification of hidden trends in data and has been used to evaluate data that have been collected about the patients seen at the clinic. This research project has explored and compared the results of two data mining techniques, using patient demographics and social history for the standard data set. The techniques that will be discussed included Supervised Learning and Unsupervised Clustering as used to search for hidden trends in the data set. The knowledge gained from the data mining session is given as a model or generalization of the data.
