Abstract
The main objective of this study is to develop a software prototype for diagnosing the risk factors and grading depression in the developing region of South East Asia especially in Bangladesh. World Health Organization (WHO) identified depression to be the most prevalent psychological disorder and according to global burden of disease survey it will be the second leading cause of long term disability. For various social constructs depression or any kind of psychiatric disorder is considered a taboo subject. Hence it is very difficult to collect data on the context of a developing country like Bangladesh. We are using a hybrid model questionnaire based on Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) and Patient Health Questionnaire (PHQ-9) by consulting psychiatric experts of Bangladesh. This study proposed a model based on Fuzzy Logic (FL). An experimental study of the system was conducted using 50 anonymous medical dataset of depression patients’ cases obtained from two experts in psychiatry from National Mental Health Institute of Bangladesh and Sheikh Mujib Medical College Hospital.
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The authors of this paper fully acknowledge the doctors, the psychiatrists and experts who have shared their valuable knowledge and help in collecting the required data, analyzing them, developing the correct system, and validating the results to make this research successful.
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Thakur, A., Sakibul Alam, M., Rashidul Hasan Abir, M., Kushal, M.A.A., Rahman, R.M. (2018). A Fuzzy Approach for the Diagnosis of Depression. In: Sieminski, A., Kozierkiewicz, A., Nunez, M., Ha, Q. (eds) Modern Approaches for Intelligent Information and Database Systems. Studies in Computational Intelligence, vol 769. Springer, Cham. https://doi.org/10.1007/978-3-319-76081-0_17
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