Towards Automated Monitoring of Parkinson's Disease Following Drug Treatment

Published in Pattern Recognition and Artificial Intelligence. ICPRAI 2022. Lecture Notes in Computer Science, vol 13364. Springer, Cham., 2022

Recommended citation: Dehsarvi, A., South Palomares, J.K., Smith, S.L. (2022). Towards Automated Monitoring of Parkinson's Disease Following Drug Treatment. In: El Yacoubi, M., Granger, E., Yuen, P.C., Pal, U., Vincent, N. (eds) Pattern Recognition and Artificial Intelligence. ICPRAI 2022. Lecture Notes in Computer Science, vol 13364. Springer, Cham. doi: 10.1007/978-3-031-09282-4_17. https://doi.org/10.1007/978-3-031-09282-4_17

This paper reports an automated approach to the clinical monitoring of Parkinson’s disease (PD) by applying Evolutionary Algorithms (EAs) to resting-state functional magnetic imaging (rs-fMRI) data. The novel application of EAs to both map and predict the functional connectivity is considered in patients receiving the drug Modafinil versus placebo.

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Recommended citation: Dehsarvi, A., South Palomares, J.K., Smith, S.L. (2022). Towards Automated Monitoring of Parkinson's Disease Following Drug Treatment. In: El Yacoubi, M., Granger, E., Yuen, P.C., Pal, U., Vincent, N. (eds) Pattern Recognition and Artificial Intelligence. ICPRAI 2022. Lecture Notes in Computer Science, vol 13364. Springer, Cham. doi:10.1007/978-3-031-09282-4_17.