Thuy T. Pham

Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings (eBook, PDF)

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 107
• Erscheinungstermin: 23. August 2018
• Englisch
• ISBN-13: 9783319986753
• Artikelnr.: 53679141

Inhaltsangabe

Introduction .- Background .- Algorithms .- Point Anomaly Detection: Application to Freezing of Gait Monitoring .- Collective Anomaly Detection: Application to Respiratory Artefact Removals.- Spike Sorting: Application to Motor Unit Action Potential Discrimination .- Conclusion .