SELDI-TOF-MS pattern analysis for cancer detection as a base for diagnostic software

Authors:
Marcin Radlak;Ryszard Klempous
Affiliations:
School of Computer Science, University of Birmingham, Edgbaston, Birmingham;Institute of Control and Optimization, Wroclaw University of Technology, Wroclaw, Poland
Venue:
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Year:
2007

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Abstract

The purpose of this paper is to present in an organized form the concept of cancer detection based on data obtained from SELDI-TOF-MS. In this paper, we outline the full process of detection: from raw data, through pre-processing towards classification. Methods and algorithms, their characteristics and suggested implementation indications are described. We aim to present the state of the art over current research. Additionally, we introduce an idea of 24h/day distributed work organization and suggest how to make the research process faster.