Risk estimation and risk prediction using machine-learning methods.

Abstract:

:After an association between genetic variants and a phenotype has been established, further study goals comprise the classification of patients according to disease risk or the estimation of disease probability. To accomplish this, different statistical methods are required, and specifically machine-learning approaches may offer advantages over classical techniques. In this paper, we describe methods for the construction and evaluation of classification and probability estimation rules. We review the use of machine-learning approaches in this context and explain some of the machine-learning algorithms in detail. Finally, we illustrate the methodology through application to a genome-wide association analysis on rheumatoid arthritis.

journal_name

Hum Genet

journal_title

Human genetics

authors

Kruppa J,Ziegler A,König IR

doi

10.1007/s00439-012-1194-y

subject

Has Abstract

pub_date

2012-10-01 00:00:00

pages

1639-54

issue

10

eissn

0340-6717

issn

1432-1203

journal_volume

131

pub_type

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