Modeling of Major Depression by Using Computational Intelligence

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Darvish, Setareh | 2010

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Type of Document: M.Sc. Thesis
Language: English
Document No: 40286 (52)
University: Sharif University of Technology, International Campus, Kish Island
Department: Science and Engineering
Advisor(s): Seifipour, Navid
Abstract:
Mental disorders are very common nowadays and affect a person’s everyday life, as well as the lives of other people around him/her. According to the World Health Organization, major depressive disorder (MDD) is considered as the fourth main cause of death and premature weakness in the whole world. Information Technology (IT) could be used to diagnose the people who are affected by the mental disorders as well as reduce their effects. As clinical decision making inherently requires reasoning under uncertainty, fuzzy logic is a suitable technique for dealing with this partial evidence. The fuzzy logic is the science of reasoning; thinking and inference that recognizes and uses the real world phenomena and it is a more appropriate modeling for major depression because it works with more qualitative variables. This thesis proposes a technique that emulates human intelligence. The methodology is developed to diagnose and predict a patient's condition and his/her next reaction to certain rules based on experience. This is a novel attempt to apply fuzzy logic techniques to model the complete cycle of major depressive behavior and its diagnosis.
Keywords:
Fuzzy Logic ; Major Depressive

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