Automatic classification of regular and irregular capnogram segments using time- and frequency-domain features: a machine learning-based approach
This paper presents a machine learning-based approach for the automatic classification of regular and irregular capnogram segments. METHODS: Herein, we proposed four time- and two frequency-domain features experimented with the support vector machine classifier through ten-fold cross-validation. MAT...
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| Format: | Article |
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IOS Press BV
2021
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