Logistic Regression in Data Mining and its Application in Identification of Disease
Pages : 3837-3839
Download PDF
Abstract
Data mining in clinical medicine deals with learning models to predict health of patients. The models is used to support clinicians in therapeutic or monitoring tasks. Data mining techniques are usually applied in clinical contexts to analyze retrospective data, thus giving professionals to check large amounts of data routinely collected during their day activity. Moreover, clinicians can take advantage of data mining techniques to deal with the amount of research results obtained by molecular medicine, which may allow transition from population-based to personalized medicine.Logistic regression is used to analyze relationships between a dichotomous dependent variable and metric or dichotomous independent variables.
Keywords: logistic regression, feature extraction, Data Mining
Article published in International Journal of Current Engineering and Technology, Vol.4, No.6 (Dec-2014)