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ŠILHAVÁ, J. SMRŽ, P.
Original Title
Additional Predictive Value of Microarray Data Compared to Clinical Variables
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
Microarrays as a promising technology for prediction of cancer diagnosis have attracted attention of many researchers in recent years. Researchers often neglect clinical data used for prediction of diagnosis compared to pre-microarray era. An important problem is determination of an additional predictive value of microarray data in relation to clinical variables. We propose a new two-step method combining logistic regression and BinomialBoosting models, to determine the additional predictive value of microarray data. This method is evaluated on two benchmark breast cancer datasets together with other already published method. The new method can combine clinical and microarray data more effectively and enables simple addition of various types of data into the combined prediction.
Keywords
logistic regression, boosting, generalized linear models, prediction, microarray data, clinical data, breast cancer
Authors
ŠILHAVÁ, J.; SMRŽ, P.
RIV year
2009
Released
9. 6. 2009
Publisher
University of Sheffield
Location
Sheffield
ISBN
978-0-9563399-0-4
Book
PRIB 2009, 4th IAPR International Conference on Pattern Recognition in Bioinformatics
Pages from
1
Pages to
6
Pages count
BibTex
@inproceedings{BUT30911, author="Jana {Šilhavá} and Pavel {Smrž}", title="Additional Predictive Value of Microarray Data Compared to Clinical Variables", booktitle="PRIB 2009, 4th IAPR International Conference on Pattern Recognition in Bioinformatics", year="2009", pages="1--6", publisher="University of Sheffield", address="Sheffield", isbn="978-0-9563399-0-4" }