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Comparisons of Discriminant Analysis Model and Generalized Logit Model in Stroke Patten Identifications Classification  

Kang, Byoung-Kab (Division of TKM Integrated Research Brain Disease Research Center, Korea Institute of Oriental Medicine)
Lee, Ju-Ah (Division of TKM Integrated Research Brain Disease Research Center, Korea Institute of Oriental Medicine)
Ko, Mi-Mi (Division of TKM Integrated Research Brain Disease Research Center, Korea Institute of Oriental Medicine)
Moon, Tae-Woong (Division of TKM Integrated Research Brain Disease Research Center, Korea Institute of Oriental Medicine)
Bang, Ok-Sun (Division of TKM Integrated Research Brain Disease Research Center, Korea Institute of Oriental Medicine)
Publication Information
Journal of Physiology & Pathology in Korean Medicine / v.25, no.2, 2011 , pp. 318-321 More about this Journal
Abstract
In this study, when a physician make a diagnosis of the Pattern Identifications(PIs) of stroke patients, the development methods of the PIs classification function is considered by diagnostic questionnaire of the PIs for stroke patients. Clinical data collected from 1,502 stroke patients who was identically diagnosed for the PIs subtypes diagnosed by two clinical experts with more than 3 years experiences in 13 oriental medical hospitals. In order to develop the classification function into PIs using the 44 items-Fire&heat(19), Qi-deficiency(11), Yin-deficiency(7), Dampness phlegm(7)- of them was significant statistically by univariate analysis in 61 questionnaires totally, we make some comparisons of the results of discriminant analysis model and generalized logit model. The overall diagnostic accuracy rate of the PIs subtypes for discriminant model(74.37%) was higher than 3% of generalized logit model(70.09%).
Keywords
Pattern Identification discrimination function; discriminant analysis model; generalized logit model; diagnosis accuracy;
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Times Cited By KSCI : 4  (Citation Analysis)
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