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Signal processing and feature selection preprocessing for classification in noisy healthcare data

Signal processing and feature selection preprocessing for classification in noisy healthcare data

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Chapter Contents:

  • 3.1 Introduction
  • 3.2 Preprocessing and database
  • 3.2.1 QRS detection
  • 3.2.2 Signal quality assessment
  • 3.2.3 Datasets
  • 3.2.4 Adding realistic noise to known data
  • 3.3 Feature extraction
  • 3.3.1 Time-domain features
  • 3.3.2 Frequency-domain features
  • 3.3.3 Nonlinear features
  • 3.4 Feature selection
  • 3.4.1 Forward likelihood ratio selection for logistic regression
  • 3.4.2 Recursive feature elimination for support vector machine
  • 3.5 Evaluation metrics
  • 3.6 Results
  • 3.6.1 Feature results comparison between AF and Non-AF
  • 3.6.2 Model development phase
  • 3.6.2.1 Logistic regression result
  • 3.6.2.2 SVM result
  • 3.6.3 Model validation phase
  • 3.7 Discussion
  • Appendix 1
  • References

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