Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings Thuy T. Pham

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Product details:

• ISBN-10 ‏ : ‎ 3319986740
• ISBN-13 ‏ : ‎ 978-3319986746
• Author: Thuy T. Pham

This book describes efforts to improve subject-independent automated classification techniques using a better feature extraction method and a more efficient model of classification. It evaluates three popular saliency criteria for feature selection, showing that they share common limitations, including time-consuming and subjective manual de-facto standard practice, and that existing automated efforts have been predominantly used for subject dependent setting. It then proposes a novel approach for anomaly detection, demonstrating its effectiveness and accuracy for automated classification of biomedical data, and arguing its applicability to a wider range of unsupervised machine learning applications in subject-independent settings.

Table of contents:

1. Introduction

2. Background

3. Algorithms

4. Point Anomaly Detection: Application to Freezing of Gait Monitoring

5. Collective Anomaly Detection: Application to Respiratory Artefact Removals

6. Spike Sorting: Application to Motor Unit Action Potential Discrimination

7. Conclusion

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