With An Innovative Application for Alzheimers Detection from Speech /
First Statement of Responsibility
by Walker H. Land Jr., J. David Schaffer.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Cham :
Name of Publisher, Distributor, etc.
Springer,
Date of Publication, Distribution, etc.
2020.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (xxii, 269 pages) :
Other Physical Details
illustrations (some color)
CONTENTS NOTE
Text of Note
Introduction -- Background for Genetic Algorithms -- Support Vector Machines (SVMs) -- The Generalized Regression Neural Network (GRNN) Oracle -- Alzheimers Disease (AD) Background -- Genetic Algorithm (GA)-SVM Paradigm -- GA-SVM Paradigm Applied to Detecting AD from Speech -- Classical Bayesian Networks (BN) MI Developed Bayesian Networks -- Generalization of MI methods -- Selected research studies -- Conclusion.
0
SUMMARY OR ABSTRACT
Text of Note
This volume presents several machine intelligence technologies, developed over recent decades, and illustrates how they can be combined in application. One application, the detection of dementia from patterns in speech, is used throughout to illustrate these combinations. This application is a classic stationary pattern detection task, so readers may easily see how these combinations can be applied to other similar tasks. The expositions of the methods are supported by the basic theory they rest upon, and their application is clearly illustrated. The books goal is to allow readers to select one or more of these methods to quickly apply to their own tasks. Includes a variety of machine intelligent technologies and illustrates how they can work together Shows evolutionary feature subset selection combined with support vector machines and multiple classifiers combined Includes a running case study on intelligent processing relating to Alzheimers / dementia detection, in addition to several applications of the machine hybrid algorithms.