Journal ArticleDOI
Selection of optimal features for classification of electrocardiograms
Reads0
Chats0
TLDR
A satisfactory and consistent overall classification accuracy was achieved by using the sequential selection algorithms for selecting continuous features by maximizing the Mahalanobis distance at each step of the feature selection process.About:
This article is published in Journal of Electrocardiology.The article was published on 1981-01-01. It has received 7 citations till now. The article focuses on the topics: Feature selection & Selection (genetic algorithm).read more
Citations
More filters
Journal ArticleDOI
Cardiac infarction injury score: an electrocardiographic coding scheme for ischemic heart disease.
TL;DR: The CIIS test results indicate that, in comparison with conventional ECG criteria for MI used in clinical trials, the diagnostic accuracy can be considerably improved by optimizing feature and threshold selection and by multivariate analysis.
Journal ArticleDOI
Comparison of the classification ability of the electrocardiogram and vectorcardiogram
TL;DR: The conventional 12-lead ECG is as good as the VCG for the differential diagnosis of 7 main entities, provided identical procedures are used in the design of the classifiers.
Journal ArticleDOI
Effective extraction of diagnostic ECG waveform information using orthonormal basis functions derived from body surface potential maps
TL;DR: The classification method described is insensitive to noise and errors in detecting QRS and T wave onsets and offsets or in selecting proper baseline for amplitude measurements and has a potential advantage particularly in serial ECG comparison.
Journal ArticleDOI
Automated electrocardiogram analysis: the state of the art.
F. Bessette,Luong Nguyen +1 more
TL;DR: Programs studied using a validated data bank provided by an international group of cardiologists show a variability not only in parameter measurement but also in diagnostic statement and in the way in which such statements are expressed.
Journal ArticleDOI
The stability of decision—Theoretic electrocardiographic classifiers based on the use of discretized features
TL;DR: With these decision-theoretic classifiers using discretized ECG features the fall in classification accuracy as a result of wrong representation of one feature rarely exceeds 20% and is usually less than 10%.
References
More filters
Journal ArticleDOI
A Branch and Bound Algorithm for Feature Subset Selection
TL;DR: In this paper, a branch and bound-based feature subset selection algorithm is proposed to select the best subset of m features from an n-feature set without exhaustive search, which is computationally computationally unfeasible.
Journal ArticleDOI
The Electrocardiogram in Population Studies A Classification System
TL;DR: A classification system for the electrocardiogram in epidemiologic studies has been developed, tested, and herein presented and permits more valid comparisons of data on heart disease between populations.
Related Papers (5)
Diagnostic accuracy of the conventional 12-lead and the orthogonal Frank-lead electrocardiograms in detection of myocardial infarctions with classifiers using continuous and Bernoulli features
Uday Jain,Pentti M. Rautaharju +1 more