Data mining is emerging as an important tool in many areas of research and industry. Companies and organizations are increasingly interested in applying data mining tools in order to increase the value added by their data collections systems. Nowhere is this potential more important than in the healthcare industry. As medical records systems become more standardized and commonplace, data quantity increases with much of it going unanalyzed. Data mining can begin to leverage some of this data into tools that help clinicians organize data and make decisions. These modeling techniques are explored in the following text. Through the use of clustering and classification techniques, accurate models of a dialysis patient's current status are derived.
Thesis
Modeling of hemodialysis patient hemoglobin: a data mining exploration
University of Iowa
Master of Science (MS), University of Iowa
Spring 2007
DOI: 10.17077/etd.2wltz072
Free to read and download, Open Access
Abstract
Details
- Title: Subtitle
- Modeling of hemodialysis patient hemoglobin: a data mining exploration
- Creators
- Michael Francis Bries - University of Iowa
- Contributors
- Andrew Kusiak (Advisor)
- Resource Type
- Thesis
- Degree Awarded
- Master of Science (MS), University of Iowa
- Degree in
- Industrial Engineering
- Date degree season
- Spring 2007
- Publisher
- University of Iowa
- DOI
- 10.17077/etd.2wltz072
- Number of pages
- x, 95 pages
- Copyright
- Copyright 2007 Michael Francis Bries
- Language
- English
- Date copyrighted
- 2007
- Description bibliographic
- Includes bibliographical references (pages 60-62).
- Academic Unit
- Industrial and Systems Engineering
- Record Identifier
- 9983777075502771
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