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This article reports the binary classification results of ADHD patients among three subgroups by using ADHD-200 dataset. We have proposed a modified feature selection approach using standard RFE-SVM model. Our results show the significance of the proposed method by making a comparison of J-statistics, F1-score and classification accuracy based on the feature selection from the original RFE-SVM vs...
In this paper, we present a classification method based on the multi-level brain partitions. Bag-of-visual-words model is used. Firstly, the representative SIFT features are extracted from brain template as the basic visual words. Secondly, individual MR images are described using the basic visual words and support vector machine classifiers are trained for different brain partitions respectively...
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