Photo of Amir Dehsarvi
    • Foresterhill, University of Aberdeen, F04 Lilian Sutton Building

      AB25 2ZD Aberdeen

      United Kingdom

    • 0 Citations
    20182018

    Research output per year

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    Personal profile

    Research Overview:

    Amir is a researcher developing automatic methods for detecting (brain imaging, speech, etc.) biomarkers for neurodegenerative diseases, such as Parkinson's disease and Alzheimer's disease, by considering the novel application of Evolutionary Algorithms.

    Currently, in his position as a Research Fellow at ABIC, Amir is working with a multidisciplinary team of clinicians and scientists who are focussed upon unravelling the mechanisms of chronic fatigue, a salient issue across the chronic disease spectrum. Specifically, he is looking into the analysis and understanding of a multi-modal MRI/fMRI brain study, using machine learning techniques (including Evolutionary Algorithms), in order to characterise the mediators of fatigue in patients with rheumatoid arthritis among other diseases.

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    Research Output

    • 1 Conference contribution

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

    Dehsarvi, A. & Smith, S. L., 31 Jul 2018, Proceedings of the Genetic and Evolutionary Computation Conference Companion on - GECCO '18. New York: Association for Computing Machinery, p. 264-265 2 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
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