Artificial Neural Network and Fuzzy Logic Approach to diagnose Autism Spectrum Disorder
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Autism Spectrum Disorder (ASD) is becoming a big issue in numerous countries around the world which can even negatively affect human natural evolution. Even though autism can be diagnosed early-before 2 years old, most children were not diagnosed with ASD until the age of 4 because of its complex symptoms and ambiguous manifestation in infant’s disorders. Applying science and technology into early autism diagnosis is of vital importance, especially when data mining branches and decision-making support systems are developing and achieving many accomplishments in various fields, medicine included. Contributing to those developments, the combination of the Artificial Neural Network (ANN) and Fuzzy logic has triggered a huge revolution in data mining and is able to solve a variety of problems. This paper is the elaboration on the method of employing this combination to facilitate the early diagnosis of ASD. The result of the paper shows that the aforementioned approach has the potential to be the fundamental basis of the supporting decision-making system in ASD researching and diagnosing.
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