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Title |
Estimation and Management of Post-Miscarriage Depression in Women Using Fuzzy Logic and Genetic Algorithm |
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Author |
Fahmida Naveed, Lahore Pakistan, Mehreen Khawar, Dr. Muhammad Rizwan, Dr. Fahad Ahmad, Dr. Kashaf Junaid |
| Citation |
Vol. 25 No. 11 pp. 63-70 |
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Abstract |
At present, a vast amount of people are suffering from mental health disorders. Mental health problems are not taken as seriously as the physical health problems. With the growing rate of miscarriages occurring, the different styles and mechanisms miscarrying-women adopt in order to overcome their grief are explored and used by an expert system based on Fuzzy Logic. The proposed method would estimate the severity of post-miscarriage depression in women using fuzzy systems and genetic algorithms. A dataset would be generated by interviewing the women suffering from post-miscarriage depression. The severity of the depression would be predicted using the variables such as the condition of the women interviewed. Fuzzy logic uses interpretability whereas genetic algorithms along with its five phases makes the production of fuzzy systems automatic and certain coping mechanisms would also be discussed which will help lower the rate of severity of depression in women. The genetic-fuzzy approach gives us optimized results. |
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Keywords |
fuzzy logic, genetic algorithm, coping mechanisms, membership functions, post-miscarriage depression |
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