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A Neuro-fuzzy Expert System For Malaria Diagnosis – The Machine Learning Approach (case Study: Accra Polyclinic)
This paper presents the use of Adaptive Neuro-Fuzzy Inference System (ANFIS) which provides a better option for Malaria diagnosis than the traditional diagnosis method which is characterized by suggestive guess work and observation of patients by doctors. Diagnosis of malaria in many cases has not been accurate by most physicians owing to factors such as tiredness and rashness and so forth, thereby leading to patients being subjected to treatment again and thereby increasing cost. The system was tested with Datasets of patients form Accra Polyclinic. The results after testing showed that ANFIS has the capability to diagnose malaria accurately and/or efficiently than the traditional approach
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