Classification of Resting-State fMRI using Evolutionary Algorithms: Towards a Brain Imaging Biomarker for Parkinson's Disease
Published in arXiv, 2019
Recommended citation: Dehsarvi, A., & Smith, S. L. (under review). "Classification of Resting-State fMRI using Evolutionary Algorithms: Towards a Brain Imaging Biomarker for Parkinson's Disease." arXiv. https://arxiv.org/abs/1910.05378
This research develops automatic methods for detecting brain imaging preclinical biomarkers for Parkinson's disease (PD) by considering the novel application of evolutionary algorithms. A fundamental novel element of this work is the use of evolutionary algorithms to both map and predict the functional connectivity in patients using resting state functional MRI data taken from the PPMI to identify PD progression biomarkers. Specifically, Cartesian Genetic Programming was used to classify DCM data as well as time-series data. Download paper here
Recommended citation: Dehsarvi, A., & Smith, S. L. (under review). “Classification of Resting-State fMRI using Evolutionary Algorithms: Towards a Brain Imaging Biomarker for Parkinson's Disease.” arXiv.