Investigating the Use of nearest-neighbour Interpolation for Cancer Research

  • We investigate in how far interpolation mechanisms based on the nearest-neighbor rule (NNR) can support cancer research. The main objective is to usethe NNR to predict the likelihood of tumorigenesis based on given risk factors.By using a genetic algorithm to optimize the parameters of the nearest-neighbourprediction, the performance of this interpolation method can be improved sub-stantially. Furthermore, it is possible to detect risk factors which are hardly ornot relevant to tumorigenesis. Our preliminary studies demonstrate that NNR-based interpolation is a simple tool that nevertheless has enough potential to beseriously considered for cancer research or related research.

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Metadaten
Author:Matthias Fuchs, Stefan Forster
URN (permanent link):urn:nbn:de:hbz:386-kluedo-528
Serie (Series number):LSA Report (97,4E)
Document Type:Preprint
Language of publication:English
Year of Completion:1997
Year of Publication:1997
Publishing Institute:Technische Universität Kaiserslautern
Faculties / Organisational entities:Fachbereich Informatik
DDC-Cassification:004 Datenverarbeitung; Informatik

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