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Fuzzy Logic means for Intelligent Diagnosis of Obstetrics Fistula Disease
Author(s) -
Amosa Babalola,
Hameed Aderemi,
Kawonise Kayode,
Ekuewa Jacob
Publication year - 2017
Publication title -
international journal of electrical electronics and computers
Language(s) - English
Resource type - Journals
ISSN - 2456-2319
DOI - 10.24001/eec.2.6.1
Subject(s) - fuzzy logic , computer science , artificial intelligence , obstetrics , medicine , machine learning
Obstetrics fistula is one of the most serious and tragic childbirth injuries. It is a hole between the birth canal and bladder or rectum caused by prolonged, obstructed labour, without access to timely, high-quality medical treatment. It leaves women leaking urine, faeces or both and often leads to chronic medical problems, depression, social isolation and deepening poverty. The goal of this research is to develop a Fuzzy logic means for intelligent diagnosis of Obstetrics fistula disease. In the study we presented the architecture of the FCM system for the diagnosis of Obstetrics Fistula. It comprises of knowledge base system, fuzzy c-means inference engine and decision support system. The knowledge base system holds the symptoms for Obstetrics Fistula. The expert system is developed in an environment characterized by Microsoft XP Professional operating system, Microsoft Access Database Management System, Visual BASIC Application Language and Microsoft Excel. Keywords-fuzzy Logic, intelligent diagnosis, childbirth injuries, obstetrics fistula.

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