Accurate detection of autism spectrum disorder from structural MRI using extended metacognitive radial basis function network
作者：
Highlights：
• A study on ASD detection in females using MRI is presented using the ABIDE dataset.
• VBM is used to study differences in gray matter composition.
• Different regions within the motor cortex area are affected for female ASD patients.
• Age-specific approach improves accuracy (by 2.5% for adolescents, 15% for adults).
• Proposed EMcRBFN classifier achieves higher accuracy than SVM and PBL-McRBFN.
摘要
•A study on ASD detection in females using MRI is presented using the ABIDE dataset.•VBM is used to study differences in gray matter composition.•Different regions within the motor cortex area are affected for female ASD patients.•Age-specific approach improves accuracy (by 2.5% for adolescents, 15% for adults).•Proposed EMcRBFN classifier achieves higher accuracy than SVM and PBL-McRBFN.
论文关键词：Autism spectrum disorder,Magnetic resonance imaging,Voxel-based morphometry feature extraction,Metacognitive radial basis function network classifier,Projection based learning algorithm,q-Gaussian activation function
论文评审过程：Available online 26 July 2015, Version of Record 6 September 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.07.031
