Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/106344
Title: A novel PBL-McRBFN-RFE approach for identification of critical brain regions responsible for Parkinson’s disease
Authors: Sateesh Babu, Giduthuri
Suresh, Sundaram
Mahanand, Belathur Suresh
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2014
Source: Sateesh Babu, G., Suresh, S., & Mahanand, B. S. (2014). A novel PBL-McRBFN-RFE approach for identification of critical brain regions responsible for Parkinson’s disease. Expert systems with applications, 41(2), 478-488.
Series/Report no.: Expert systems with applications
Abstract: In this paper, we present a novel approach for the identification of critical brain regions responsible for Parkinson’s disease (PD) based on magnetic resonance images (MRI) using meta-cognitive radial basis function network (McRBFN) classifier with Recursive Feature Elimination (RFE). The McRBFN classifier uses voxel based morphometric (VBM) features extracted from MRI and employs a projection based learning (PBL) algorithm. The meta-cognitive learning present in PBL-McRBFN helps in selecting proper samples to learn based on its current knowledge and evolve the architecture automatically. Since, the classifier developed using PBL-McRBFN is efficient, we propose recursive feature elimination approach (called PBL-McRBFN-RFE) to identify most relevant brain regions responsible for PD prediction. The study has been conducted using the Parkinson’s Progression Markers Initiative (PPMI) data set. First, we conducted the study on PD prediction using the PBL-McRBFN classifier on the PPMI data set. We have also compared the results of the PBL-McRBFN classifier with the support vector machine (SVM) classifier. The study results clearly show that the PBL-McRBFN classifier produces better generalization performance on PD prediction. Finally, we use RFE approach with PBL-McRBFN to identify the brain regions responsible for PD. The PBL-McRBFN-RFE selected features indicate that the loss of gray matter in the superior temporal gyrus region may be responsible for the onset of PD, and is consistent with the earlier findings from medical research studies.
URI: https://hdl.handle.net/10356/106344
http://hdl.handle.net/10220/17973
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2013.07.073
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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