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Statistical pattern recognition for ...

Parsons, Thomas D.

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Statistical pattern recognition for breast cancer research: Comparison of theory-driven general linear model methodologies with data-driven artificial neural network architectures.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical pattern recognition for breast cancer research: Comparison of theory-driven general linear model methodologies with data-driven artificial neural network architectures./
Author:	Parsons, Thomas D.
Description:	420 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5249.
Contained By:	Dissertation Abstracts International64-10B.
Subject:	Psychology, Cognitive. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3110202

Statistical pattern recognition for breast cancer research: Comparison of theory-driven general linear model methodologies with data-driven artificial neural network architectures.
Parsons, Thomas D.

Statistical pattern recognition for breast cancer research: Comparison of theory-driven general linear model methodologies with data-driven artificial neural network architectures. - 420 p.

Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5249.

Thesis (Ph.D.)--Fuller Theological Seminary, School of Psychology, 2004.

Medical informatic data analysis aims at mining databases for knowledge discovery using statistical pattern recognition methodologies. Medical informatic researchers use knowledge discovered from databases to make predictions and classificationsSubjects--Topical Terms:

1017810
Psychology, Cognitive.

Statistical pattern recognition for breast cancer research: Comparison of theory-driven general linear model methodologies with data-driven artificial neural network architectures.
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500 $a Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5249.
500 $a Chair: J. Galen Buckwalter.
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