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
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.
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.
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.
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