Chapter 11 Outlier detection in biomedical data: ECG-focused approaches
-
Ekin Can Erkuş
Abstract
Outliers are among the most important data behaviors in time series data and have exceptional importance in biomedical data analyses. They may either represent an unwanted problematic aspect or a core data behavior. Detecting and correcting the problematic samples in data may improve further analyses such as model performance and diagnostic accuracy. On the other hand, locating the outlying samples in the main data behavior may help with pattern recognition in the data. Therefore, the outlier detection step in the preliminary analysis holds a critical key to the rest of the analyses. This chapter investigates the three types of outliers found in the biomedical data by providing examples from the electrocardiography data modality.
Abstract
Outliers are among the most important data behaviors in time series data and have exceptional importance in biomedical data analyses. They may either represent an unwanted problematic aspect or a core data behavior. Detecting and correcting the problematic samples in data may improve further analyses such as model performance and diagnostic accuracy. On the other hand, locating the outlying samples in the main data behavior may help with pattern recognition in the data. Therefore, the outlier detection step in the preliminary analysis holds a critical key to the rest of the analyses. This chapter investigates the three types of outliers found in the biomedical data by providing examples from the electrocardiography data modality.
Chapters in this book
- Frontmatter I
- Contents V
- List of authors VII
- Chapter 1 Use of digital systems in the design system of photovoltaic solar stations 1
- Chapter 2 Potential wind energy in Turkmenistan 21
- Chapter 3 Potential of using biogas technology in Turkmenistan 31
- Chapter 4 Energy efficiency 45
- Chapter 5 Latent renewable energy in Turkmenistan 57
- Chapter 6 Approximate stochastic simulation algorithms 67
- Chapter 7 The role of supply chain management in the construction industry 95
- Chapter 8 Selection of threshold in binary graphs of biological networks 121
- Chapter 9 Model selection criteria with bootstrap algorithms: applications in biological networks 133
- Chapter 10 Technocracy in Governance: new directions in city functioning and urban planning 149
- Chapter 11 Outlier detection in biomedical data: ECG-focused approaches 161
- Chapter 12 Optimization of debt collection strategies for South African banks with machine learning models 183
- Chapter 13 Performance of six turbulence models in predicting two-phase flow on a hydraulic test bench 209
- Index 231
Chapters in this book
- Frontmatter I
- Contents V
- List of authors VII
- Chapter 1 Use of digital systems in the design system of photovoltaic solar stations 1
- Chapter 2 Potential wind energy in Turkmenistan 21
- Chapter 3 Potential of using biogas technology in Turkmenistan 31
- Chapter 4 Energy efficiency 45
- Chapter 5 Latent renewable energy in Turkmenistan 57
- Chapter 6 Approximate stochastic simulation algorithms 67
- Chapter 7 The role of supply chain management in the construction industry 95
- Chapter 8 Selection of threshold in binary graphs of biological networks 121
- Chapter 9 Model selection criteria with bootstrap algorithms: applications in biological networks 133
- Chapter 10 Technocracy in Governance: new directions in city functioning and urban planning 149
- Chapter 11 Outlier detection in biomedical data: ECG-focused approaches 161
- Chapter 12 Optimization of debt collection strategies for South African banks with machine learning models 183
- Chapter 13 Performance of six turbulence models in predicting two-phase flow on a hydraulic test bench 209
- Index 231
