Robust optimization of convolutional neural networks with a uniform experiment design method: a case of phonocardiogram testing in patients with heart diseases

Robust optimization of convolutional neural networks with a uniform experiment design method: a case of phonocardiogram testing in patients with heart diseases

Background: Heart sound measurement is crucial for analyzing and diagnosing patients with heart diseases. This study employed phonocardiogram signals as the input signal for heart disease analysis due to the accessibility of the respective method. This study referenced preprocessing techniques propo...

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Bibliographic Details
Main Authors: Chang, P.-C (Author), Chou, F.-I (Author), Chou, J.-H (Author), Ho, W.-H (Author), Huang, T.-H (Author), Qu, J.-Y (Author), Tsai, J.-T (Author), Yang, P.-Y (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
artificial intelligence
Artificial Intelligence
Cardiology
Chemical activation
Convolution
Convolutional neural network
Convolutional neural networks
Design
Design method
diagnostic imaging
Diseases
Forecasting
Gradient methods
Heart
heart disease
Heart disease
Heart Diseases
Heart sounds
human
Humans
Hyper-parameter
Neural Networks, Computer
Optimization
Optimization problems
Patient treatment
Phonocardiogram
Phonocardiograms
Phonocardiography
Robust optimization
Stochastic models
Stochastic systems
Uniform design
Uniform experiment designs
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