Survival analysis with Cox regression and random non-linear projections

Samuel Branders, Benoît Frénay, Pierre Dupont

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Abstract

Proportional Cox hazard models are commonly used in survival analysis, since they define risk scores which can be directly interpreted in terms of hazards. Yet they cannot account for non-linearities in their covariates. This paper shows how to use random non-linear projections to efficiently address this limitation.

Original languageEnglish
Title of host publication23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2015 - Proceedings
Publisheri6doc.com publication
Pages119-124
Number of pages6
ISBN (Electronic)9782875870148
Publication statusPublished - 2015
Event23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2015 - Bruges, Belgium
Duration: 22 Apr 201524 Apr 2015

Conference

Conference23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2015
CountryBelgium
CityBruges
Period22/04/1524/04/15

Fingerprint Dive into the research topics of 'Survival analysis with Cox regression and random non-linear projections'. Together they form a unique fingerprint.

  • Cite this

    Branders, S., Frénay, B., & Dupont, P. (2015). Survival analysis with Cox regression and random non-linear projections. In 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2015 - Proceedings (pp. 119-124). i6doc.com publication.