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In this paper, a novel framework for global diagnosis of autism spectrum disorder (ASD) using task-based functional MRI data is presented. A speech fMRI experiment is held to obtain local features related to the functional activity of the brain. This study proposes both global diagnosis and local diagnosis by analyzing brain brainnetome atlas (BNT) which will lead to the first step of providing personalized medicine. The diagnosis pipeline consists of four steps on functional MRI volumes. The experimental results show that the global classification accuracy of our framework is about 75.8% and is much higher than other alternatives. Finally, comprehensive brain maps are provided for different individuals to indicate the degree of susceptibility of each brain area for autism, moving towards the idea of personalized medicine.