An innovative method for cardiovascular disease detection based on nonlinear geometric features and feature reduction combination

Abstract

Cardiovascular is arguably the most dominant death cause in the world. Heart functionality can be measured in various ways. Heart sounds are usually inspected in these experiments as they can unveil a variety of heart related diseases. This study tackles the lack of reliable models and high training times on a publicly available dataset. The heart sound set is provided by Physionet consisting of 3153 recordings, from which five seconds were fixed to evaluate to the developed method. In this work, we propose a novel method based on feature reduction combination, using Genetic Algorithm (GA) and Principal Component Analysis (PCA). The authors present eight dominant features in heart sound classification: mean duration of systole interval, the standard deviation of diastole interval, the absolute amplitude ratio of diastole to S2, S1 to systole and S1 to diastole, zero crossings, Centroid to Centroid distance (CCdis) and mean power in the 95–295 Hz range. These reduced features are then optimized respectively with two straightforward classification algorithms weighted k-NN with a lower-dimensional feature space and Linear SVM that uses a linear combination of all features to create a robust model, acquiring up to 98.15% accuracy, holding the best stats in the heart sound classification on a largely used dataset. According to the experiments done in this study, the developed method can be further explored for real world heart sound assessments.

[Retracted] Design and Research of Mathematics Teaching Intelligent Classroom Based on PCA‐NN Algorithm

“…Sun et al studied the classroom comprehensive evaluation from the mathematical model, the classification of mathematics teaching contents, and mathematics exercises after class and adopted different teaching strategies for experimental teaching [ 12 ]. Saeedi et al showed that the teaching method has good stability in improving the quality of mathematics teaching and is suitable for the formulation of the optimal teaching plan [ 13 ]. In order to improve the teaching efficiency and overall stability of mathematics teaching classroom, through the research and analysis of different students, a hierarchical teaching method is proposed based on mathematics teaching theory [ 14 ].…”