Gene expression feature selection for prostate cancer diagnosis using a two-phase heuristic-deterministic search strategy.
作者： Saleh Shahbeig , Akbar Rahideh , Mohammad Sadegh Helfroush , Kamran Kazemi
DOI: 10.1049/IET-SYB.2017.0044
关键词:
摘要: Here, a two-phase search strategy is proposed to identify the biomarkers in gene expression data set for prostate cancer diagnosis. A statistical filtering method initially employed remove noisiest data. In first phase of strategy, multi-objective optimisation based on binary particle swarm algorithm tuned by chaotic select optimal subset genes with minimum number and maximum classification accuracy. Finally, second cache-based modification sequential forward floating selection used find most discriminant from selected phase. The results applying available challenging demonstrate that can perfectly informative such accuracy, sensitivity, specificity 100% are achieved only nine biomarkers.
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