Name
Abstract | ||
|---|---|---|
In this paper we present the results of an intelligent analysis of osteoporosis database gathered during a longitudinal study in which a random sample of 100 women who had passed precautionary examinations for detection of osteoporosis over five years and were not referred for a definite medical diagnosis was pulled from the records. The intelligent data analysis using advanced methods for decision tree construction was used in order to try to find the main factors that can reduce the risk for development of osteoporosis in women. Most of the extracted knowledge confirmed known medical criteria that put women to risk for osteoporosis, however some new interesting patterns have also been shown. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/CBMS.2003.1212821 | CBMS |
Keywords | Field | DocType |
longitudinal study,intelligent data analysis,women,advanced method,diseases,definite medical diagnosis,decision tree construction,precautionary examinations,data analysis,main factor,human bone density,bone,osteoporosis database,new interesting pattern,intelligent analysis,information services,density measurement,medical criterion,known medical criteria,medical diagnostic computing,decision trees,medical expert systems,medical diagnosis,intelligence analysis,random sampling,databases,decision tree | Information system,Decision tree,Data mining,Longitudinal study,Computer science,Bone density,Medical physics,Osteoporosis,Medical diagnosis,Pathology | Conference |
ISSN | ISBN | Citations |
1063-71258 | 0-7695-1901-6 | 0 |
PageRank | References | Authors |
0.34 | 1 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Petra Povalej | 1 | 24 | 5.70 |
| Mitja Lenič | 2 | 41 | 5.88 |
| Milan Zorman | 3 | 57 | 13.07 |
| Peter Kokol | 4 | 309 | 74.52 |
| Margaret G. E. Peterson | 5 | 0 | 0.68 |
| Joseph M. Lane | 6 | 0 | 0.68 |