Selection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.

Selection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.

Blog Article

Identification of risk factors in patients with a particular disease can be analyzed in clinical data sets by using feature selection procedures of pattern recognition and granular foveolae data mining methods.The applicability of the relaxed linear separability (RLS) method of feature subset selection was checked for high-dimensional and mixed type (genetic and phenotypic) clinical data of patients first due helmet with end-stage renal disease.The RLS method allowed for substantial reduction of the dimensionality through omitting redundant features while maintaining the linear separability of data sets of patients with high and low levels of an inflammatory biomarker.The synergy between genetic and phenotypic features in differentiation between these two subgroups was demonstrated.