Computational support system for personalized medicine
Ganesh Kumar Pugalendhi, Ku‐Jin Kim · 2015
The abundance of genes with the scarcity of samples tending towards a convinced group of disease stresses physician during the personalized medicine treatment. This paper suggests an amalgamation of different intelligent techniques to comprehend the patient's genetic information during multicategory diagnosis. An improved fuzzy rough set based on lower approximation is proposed to compute f-information extrinsically to filter gene subset. Water swirl algorithm inspired by the water movement in the sink is recommended to identify potential genes intrinsically using fuzzy rule based decision support system.