Abstract:
Autism Spectrum Disorder (ASD) is a clinically heterogeneous neurological developmental
disorder. It is called a spectrum disorder because of its range of symptoms. Early diagnosis and proper
intervention is required for the effective treatment of autism. Diagnosis is based on the quantitative
and qualitative analysis made by the clinician. The expertise of the clinician is so important in the
proper diagnosis and classification of autism. This paper proposes an Expert system that act as a
support system to the clinician. Major clinical attributes of autism along with facial features are used
as input to the expert system. The main highlight is the use of feautures from 3D facial imagery for
autism classification. The expert system operates in two modes, diagnosis mode and grading mode.
Naïve Bayes classifier is initially used for diagnosis mode where as overall system is implemented
using a Neuro-Fuzzy approach. In the diagnosis mode 100% accuracy and in classification mode
98.8% accuracy is obtained.
