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Neural Networks and Other Machine Learning Methods in Cancer Research.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Pandu Rangan, C.
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Sandoval, Francisco
Prieto, Alberto
Cabestany, Joan
Graña, Manuel
Vellido, Alfredo
Source :
Computational & Ambient Intelligence; 2007, p964-971, 8p
Publication Year :
2007

Abstract

Evidence-based medicine has grown in stature over the last three decades and is now regarded a key development of modern medicine. The evidence base can be heterogeneous, involving both qualitative knowledge and measured quantitative data. Machine Learning (ML) methods have also begun to establish themselves as an alternative and promising approach to computer-based data analysis in oncology, as this field moves gradually away from being the preserve of traditional statistical analysis. In this paper, we describe the main areas of cancer research in which ML methods are currently being applied, and briefly discuss some of the advantages and disadvantages of their application. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540730064
Database :
Complementary Index
Journal :
Computational & Ambient Intelligence
Publication Type :
Book
Accession number :
33147792
Full Text :
https://doi.org/10.1007/978-3-540-73007-1_116