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A Biomedical System Based on Artificial Neural Network and Principal Component Analysis for Diagnosis of the Heart Valve Diseases

https://doi.org/10.1007/s10916-010-9446-7
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Principal Component Analysis
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Principal Component Analysis
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Classifying coronary dysfunction using neural networks through cardiovascular auscultation
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Artificial neural network detects changes in electro-encephalogram power spectrum of different sleep-wake states in an animal model of heat stress
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Computer-Based Detection and Analysis of Heart Sound and Murmur
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Diagnosing Aortic Valve Stenosis by Parameter Extraction of Heart Sound Signals
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Backpropagation Artificial Neural Network Classifier to Detect Changes in Heart Sound due to Mitral Valve Regurgitation
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The parsimony principle applied to multivariate calibration
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Selection of components in principal component analysis: A comparison of methods
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A computerized diagnostic system for the interpretation of umbilical artery blood flow velocity waveforms
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A classifier based on the artificial neural network approach for cardiologic auscultation in pediatrics
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A cardiac sound characteristic waveform method for in-home heart disorder monitoring with electric stethoscope
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Classification of mitral stenosis from Doppler signals using short time Fourier transform and artificial neural networks
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Analysis of EEG signals during epileptic and alcoholic states using AR modeling techniques
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Heart sound analysis for symptom detection and computer-aided diagnosis
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Artificial neural networks based on principal component analysis input selection for clinical pattern recognition analysis
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Neural classification of lung sounds using wavelet coefficients
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Feature extraction and dimensionality reduction algorithms and their applications in vowel recognition
inferredcites →https://doi.org/10.1016/s0146-2806(00)70005-3openalex-snapshot
Foreword
inferredcites →https://doi.org/10.1016/s0167-7012(00)00201-3openalex-snapshot
Artificial neural networks: fundamentals, computing, design, and application
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Classification of heart sounds using an artificial neural network
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Selection of the Number of Principal Components: The Variance of the Reconstruction Error Criterion with a Comparison to Other Methods
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Applications of neural networks in structure-activity relationships of a small number of molecules
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Application of Periodogram and AR Spectral Analysis to EEG Signals
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Classification of heart sounds using time-frequency method and artificial neural networks
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A new look at the statistical model identification
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What is the fast Fourier transform?
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Analysis and classification of heart sounds and murmurs based on the instantaneous energy and frequency estimations
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Signal Detectability
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A decision tree – based method for the differential diagnosis of Aortic Stenosis from Mitral Regurgitation using heart sounds
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Classification of the heart sounds via artificial neural network

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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