Amir Dehsarvi

Amir Dehsarvi

I am a researcher interested in the application of machine learning techniques for the analysis of medical data.

Classification of resting-state fMRI for olfactory dysfunction in Parkinson's disease using evolutionary algorithms.

Published in Proceedings of the Genetic and Evolutionary Computation Conference Companion on - GECCO '18, 2018

Recommended citation: Dehsarvi, A., & Smith, S. L. (2018). "Classification of resting-state fMRI for olfactory dysfunction in Parkinson's disease using evolutionary algorithms." Proceedings of the Genetic and Evolutionary Computation Conference Companion on - GECCO '18. New York, New York, USA: ACM Press. https://doi.org/10.1145/3205651.3205681

This paper develops automatic methods for detecting brain imaging preclinical biomarkers for olfactory dysfunction in early stage Parkinson's disease (PD) by considering the novel application of evolutionary algorithms. Classification will be applied to PD patients with severe hyposmia, patients with no/mild hyposmia, and healthy controls..

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Recommended citation: Dehsarvi, A., & Smith, S. L. (2018). “Classification of resting-state fMRI for olfactory dysfunction in Parkinson&#39s disease using evolutionary algorithms.” Proceedings of the Genetic and Evolutionary Computation Conference Companion on - GECCO '18. New York, New York, USA: ACM Press.