Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings [electronic resource] /
Pham, Thuy T.author.
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.
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 .
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.
Biomedical engineering.
Data mining.
Computational intelligence.
Bioinformatics.
Biomedical Engineering and Bioengineering.
Data Mining and Knowledge Discovery.
Computational Intelligence.
Bioinformatics.