Are You Becoming a Diabetic? A Data Mining Approach
- 1 January 2009
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 43, 18-22
- https://doi.org/10.1109/fskd.2009.807
Abstract
Data today is accumulated in a fast pace. This makes traditional data analysis methods impractical. Data mining (DM) presents an innovative approach to address this problem. This study use DM techniques to identify diabetic patients of a large healthcare enterprise. Consequently, we show the benefits of taking the DM method to identify patients.Keywords
This publication has 19 references indexed in Scilit:
- Creating Knowledge for Business Decision MakingPublished by IGI Global ,2011
- Lot-sizing two-echelon assembly systems with random yields and rigid demandEuropean Journal of Operational Research, 2006
- Introduction to the special issue on successful real-world data mining applicationsACM SIGKDD Explorations Newsletter, 2006
- Data mining for improved cardiac careACM SIGKDD Explorations Newsletter, 2006
- Healthcare Knowledge ManagementPublished by IGI Global ,2006
- A selective data retention approach in massive databasesOmega, 2004
- Multiple Lotsizing in Production to Order with Random Yields: Review of Recent AdvancesAnnals of Operations Research, 2004
- A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification AlgorithmsMachine Learning, 2000
- The KDD process for extracting useful knowledge from volumes of dataCommunications of the ACM, 1996
- Information as inventory: A new conceptual viewInformation & Management, 1991