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Combining Gene Expression and Clinical Data to Increase Performance of Prognostic Breast Cancer Models

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F12%3APU101906" target="_blank" >RIV/00216305:26230/12:PU101906 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Combining Gene Expression and Clinical Data to Increase Performance of Prognostic Breast Cancer Models

  • Original language description

    Microarray class prediction is an important application of gene expression data in biomedical research. Combining gene expression data with other relevant data may add valuable information and can generate more accurate prognostic predictions. In this paper, we combine gene expression data with clinical data. We use logistic regression models that can be built through various regularized techniques. Generalized linear models enables combining of these models with different structure of data. Our two suggested approaches are evaluated with publicly available breast cancer data sets. Based on the results, our approaches have a positive effect on prediction performances and are not computationally intensive.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/TA01010931" target="_blank" >TA01010931: System for FISH analysis evaluation support</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2012

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    4th International Conference on Agents and Artificial Intelligence

  • ISBN

    978-989-8425-95-9

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    1-6

  • Publisher name

    Institute for Systems and Technologies of Information, Control and Communication

  • Place of publication

    Algarve

  • Event location

    Algarve

  • Event date

    Feb 6, 2012

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article