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Machine Learning in Healthcare Informatics: Intelligent Systems Reference Library, cartea 56

Editat de Sumeet Dua, U. Rajendra Acharya, Prerna Dua
en Limba Engleză Paperback – 3 sep 2016
The book is a unique effort to represent a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. The book provides a unique compendium of current and emerging machine learning paradigms for healthcare informatics and reflects the diversity, complexity and the depth and breath of this multi-disciplinary area. The integrated, panoramic view of data and machine learning techniques can provide an opportunity for novel clinical insights and discoveries.
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Specificații

ISBN-13: 9783662507636
ISBN-10: 3662507633
Pagini: 344
Ilustrații: XII, 332 p. 119 illus., 50 illus. in color.
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.49 kg
Ediția:Softcover reprint of the original 1st ed. 2014
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Intelligent Systems Reference Library

Locul publicării:Berlin, Heidelberg, Germany

Cuprins

From the Contents.- Introduction to Machine Learning in Healthcare Informatics.- Wavelet-Based Machine Learning Techniques for ECG Signal Analysis.- Application of Fuzzy Logic Control for Regulation of Glucose Level of Diabetic Patient.- A Study on Machine Learning in EEG Signal Analysis.

Textul de pe ultima copertă

The book is a unique effort to represent a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. The book provides a unique compendium of current and emerging machine learning paradigms for healthcare informatics and reflects the diversity, complexity and the depth and breath of this multi-disciplinary area. The integrated, panoramic view of data and machine learning techniques can provide an opportunity for novel clinical insights and discoveries.

Caracteristici

Provides a unique compendium of current and emerging machine learning paradigms for healthcare informatics First reference in the interdisciplinary area of healthcare informatics and machine learning Written by leading experts in the field Includes supplementary material: sn.pub/extras