![](/images/graphics-bg.png)
The Study of Misclassification Probability in Discriminant Model of Pattern Identification for Stroke
Joint Authors
Source
Evidence-Based Complementary and Alternative Medicine
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-03-10
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Background.
Pattern identification (PI) is the basic system for diagnosis of patients in traditional Korean medicine (TKM).
The purpose of this study was to identify misclassification objects in discriminant model of PI for improving the classification accuracy of PI for stroke.
Methods.
The study included 3306 patients with stroke who were admitted to 15 TKM hospitals from June 2006 to December 2012.
We derive the four kinds of measure (D, R, S, and C score) based on the pattern of the profile graphs according to classification types.
The proposed measures are applied to the data to evaluate how well those detect misclassification objects.
Results.
In 10–20% of the filtered data, misclassification rate of C score was highest compared to those rates of other scores (42.60%, 41.15%, resp.).
In 30% of the filtered data, misclassification rate of R score was highest compared to those rates of other scores (40.32%).
And, in 40–90% of the filtered data, misclassification rate of D score was highest compared to those rates of other scores.
Additionally, we can derive the same result of C score from multiple regression model with two independent variables.
Conclusions.
The results of this study should assist the development of diagnostic standards in TKM.
American Psychological Association (APA)
Ko, Mi Mi& Kim, Honggie. 2016. The Study of Misclassification Probability in Discriminant Model of Pattern Identification for Stroke. Evidence-Based Complementary and Alternative Medicine،Vol. 2016, no. 2016, pp.1-15.
https://search.emarefa.net/detail/BIM-1103939
Modern Language Association (MLA)
Ko, Mi Mi& Kim, Honggie. The Study of Misclassification Probability in Discriminant Model of Pattern Identification for Stroke. Evidence-Based Complementary and Alternative Medicine No. 2016 (2016), pp.1-15.
https://search.emarefa.net/detail/BIM-1103939
American Medical Association (AMA)
Ko, Mi Mi& Kim, Honggie. The Study of Misclassification Probability in Discriminant Model of Pattern Identification for Stroke. Evidence-Based Complementary and Alternative Medicine. 2016. Vol. 2016, no. 2016, pp.1-15.
https://search.emarefa.net/detail/BIM-1103939
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1103939