After a brief introduction to statistical decision theory, the paper describes the approximation of the probability p(x, 0 of a measurement vector x and a diagnostic category i by a linear function in x using multiple multivariate regression techniques. The classification algorithm thus obtained is evaluated for increasing number of predictive measurements in terms of the percentage of correct classification for each diagnostic category, the overall percentage of correct classification and the sensitivity and specificity. For a fixed number of 16 ECG—VCG measurements the classification method is characterized by its misclassification matrix and its diagnostic operating curve. Based on a large test set of cases containing single and mixed diagnoses it could be shown that the algorithm gives very good results not only for single diagnostic cases but also in those situations where patients have several pathological conditions at a time.
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1 March 1978
Review Article|
March 01 1978
WAVE MORPHOLOGICAL CLASSIFICATION OF ECG—VCG's USING A LINEAR REGRESSION TECHNIQUE Available to Purchase
CLAUS‐E. LIEDTKE;
CLAUS‐E. LIEDTKE
Division of Health Computer Sciences and Section of Cardiology, Department of Medicine, University of Minnesota, Box 511, Mayo Memorial Building, Minneapolis, Minnesota 55455, USA
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NAIP TUNA
NAIP TUNA
Division of Health Computer Sciences and Section of Cardiology, Department of Medicine, University of Minnesota, Box 511, Mayo Memorial Building, Minneapolis, Minnesota 55455, USA
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Publisher: Emerald Publishing
Online ISSN: 1758-7883
Print ISSN: 0368-492X
© MCB UP Limited
1978
Kybernetes (1978) 7 (3): 189–194.
Citation
LIEDTKE C, TUNA N (1978), "WAVE MORPHOLOGICAL CLASSIFICATION OF ECG—VCG's USING A LINEAR REGRESSION TECHNIQUE". Kybernetes, Vol. 7 No. 3 pp. 189–194, doi: https://doi.org/10.1108/eb005483
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