Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings

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, includ...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Pham, Thuy T. (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Σειρά:Springer Theses, Recognizing Outstanding Ph.D. Research,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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300 |a XV, 107 p. 35 illus., 32 illus. in color.  |b online resource. 
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505 0 |a 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 . 
520 |a 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. 
650 0 |a Biomedical engineering. 
650 0 |a Data mining. 
650 0 |a Computational intelligence. 
650 0 |a Bioinformatics. 
650 1 4 |a Biomedical Engineering and Bioengineering.  |0 http://scigraph.springernature.com/things/product-market-codes/T2700X 
650 2 4 |a Data Mining and Knowledge Discovery.  |0 http://scigraph.springernature.com/things/product-market-codes/I18030 
650 2 4 |a Computational Intelligence.  |0 http://scigraph.springernature.com/things/product-market-codes/T11014 
650 2 4 |a Bioinformatics.  |0 http://scigraph.springernature.com/things/product-market-codes/L15001 
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