Comparison of discriminant analysis and probabilistic expert system in VCG data classification

Title:

Comparison of discriminant analysis and probabilistic expert system in VCG data classification

Creator:

Valová, D., Drška, Z., Polánková, M., and Málková, A.

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:6ee7dd1b-f8e5-4e5f-a3b7-44370247fc1a
uuid:6ee7dd1b-f8e5-4e5f-a3b7-44370247fc1a

Subject:

probabilistic expert system, discriminant analysis, vectorcardiogram, and ischaemic heart disease

Type:

article, model:article, and TEXT

Description:

Our previous studies (Valová et al. 1992) have dealt with the possibilities of expert system utilization for electrocardiologic data interpretation. The results obtained in these studies provided evidence that the selected probabilistic expert system is suitable for the solution of VCG data interpretation problems. The aim of this paper was to compare the results obtained by stepwise discriminant analysis with that obtained by a probabilistic expert system. These classification methods were applied to VCG data measured by Frank's lead system. Five groups of patients were investigated: 76 healthy subjects, 36 patients with angina pectoris, 112 patients with old posterior myocardial infarction, 107 patients with old anterior myocardial infarction and 35 patients with old anteroseptal myocardial infarction. The classification was carried out by the leaving-one-out technique. Results of the classification obtained in five groups by a probabilistic expert system are evidently better than those obtained by stepwise discriminant analysis.

Language:

English

Rights:

http://creativecommons.org/licenses/by-nc-sa/4.0/
policy:public

Source:

Physiological research | 1993 Volume:42 | Number:2

Harvested from:

CDK

Metadata only:

false