Computational learning approaches to data analytics in biomedical applications

Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and...

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Bibliographische Detailangaben
Hauptverfasser: Al-Jabery, Khalid, Obafemi-Ajayi, Tayo, Olbricht, Gayla, Wunsch, Donald C.
Format: E-Book Buch
Sprache:Englisch
Veröffentlicht: Amsterdam Academic Press 2020
Elsevier Science & Technology
Ausgabe:1
Schlagworte:
Big data
Bioinformatics
Biomedical engineering
Biomedical engineering > Data processing
Computational biology
Computational learning theory
Medicine
Medicine > Data processing
ISBN:9780128144824, 0128144823
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and connections between statistical analysis and clustering. The book introduces and discusses the major problems relating to data analytics, provides a review of influential and state-of-the-art learning algorithms for biomedical applications, reviews cluster validity indices and how to select the appropriate index, and includes an overview of statistical methods that can be applied to increase confidence in the clustering framework and analysis of the results obtained.
ISBN:9780128144824
0128144823
DOI:10.1016/C2016-0-04633-8