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This book points out to logistic regression analysis in fuzzy environment. In this regard, three clinical situations are considered with a proposed method for each one. First and second methods model fuzzy diagnosis based on a set of non fuzzy (crisp) variables by using a real number and a fuzzy number for the possibility of being ill, respectively. The third model is proposed for a situation of no ambiguities in diagnosis but in the relations among the variables.

Produktbeschreibung
This book points out to logistic regression analysis in fuzzy environment. In this regard, three clinical situations are considered with a proposed method for each one. First and second methods model fuzzy diagnosis based on a set of non fuzzy (crisp) variables by using a real number and a fuzzy number for the possibility of being ill, respectively. The third model is proposed for a situation of no ambiguities in diagnosis but in the relations among the variables.
Autorenporträt
She is faculty member of Biostatistics Department at Shiraz University of Medical Sciences in Iran. Her researches are modelling in Fuzzy environments, neural networks, nonlinear and linear relations in ccrisp environments and their clinical applications.