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GMDS 2013: 58. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

01. - 05.09.2013, Lübeck

Biomarker selection in profiles of varying dimensionality

Meeting Abstract

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  • Hans Kestler - Research Group Bioinformatics and Systems Biology, Ulm University, Ulm, DE

GMDS 2013. 58. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Lübeck, 01.-05.09.2013. Düsseldorf: German Medical Science GMS Publishing House; 2013. DocAbstr.315

doi: 10.3205/13gmds280, urn:nbn:de:0183-13gmds2802

Published: August 27, 2013

© 2013 Kestler.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.


Outline

Text

Introduction: In recent years, high-throughput methods have become standard tools in clinical investigations. Specialized machine learning methods allow for the analysis of these high-dimensional patterns for identifying biomarker combinations that are related to specific phenotypes. Such marker combinations can aid in the identification of new disease subtypes and provide decision support for diagnoses.

Methods: The talk presents supervised machine learning techniques that target specific issues in clinical studies. It covers the identification of relevant biomarkers in high-throughput scenarios as well as specialized classifiers. In particular, a classifier that chooses representative subjects that are prototypic for certain subgroups is introduced.

Results: The new methods showed their usefulness in different clinical studies. Theoretical results show that such methods are well-suited for clinical datasets of low cardinality.

Discussion: Depending on the particular study setting, the employed methods must meet different requirements. The talk highlights some particular aspects and proposes suitable approaches. In practice, these may be further adapted to the particular requirements of a study.


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