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A Novel Approach for Cognitive Clustering of Parkinsonisms through Affinity Propagation

Neuroscience Research Center, Magna Graecia University, 88100 Catanzaro, Italy
Institute of Neurology, Department of Medical and Surgical Sciences, Magna Graecia University, 88100 Catanzaro, Italy
Neuroimaging Research Unit, Institute of Molecular Bioimaging and Physiology, National Research Council, 88100 Catanzaro, Italy
Author to whom correspondence should be addressed.
Academic Editor: Luca Becchetti
Algorithms 2021, 14(2), 49;
Received: 12 January 2021 / Revised: 29 January 2021 / Accepted: 1 February 2021 / Published: 4 February 2021
(This article belongs to the Special Issue Machine Learning in Healthcare and Biomedical Application)
Cluster analysis is widely applied in the neuropsychological field for exploring patterns in cognitive profiles, but traditional hierarchical and non-hierarchical approaches could be often poorly effective or even inapplicable on certain type of data. Moreover, these traditional approaches need the initial specification of the number of clusters, based on a priori knowledge not always owned. For this reason, we proposed a novel method for cognitive clustering through the affinity propagation (AP) algorithm. In particular, we applied the AP clustering on the regression residuals of the Mini Mental State Examination scores—a commonly used screening tool for cognitive impairment—of a cohort of 49 Parkinson’s disease, 48 Progressive Supranuclear Palsy and 44 healthy control participants. We found four clusters, where two clusters (68 and 30 participants) showed almost intact cognitive performance, one cluster had a moderate cognitive impairment (34 participants), and the last cluster had a more extensive cognitive deficit (8 participants). The findings showed, for the first time, an intra- and inter-diagnostic heterogeneity in the cognitive profile of Parkinsonisms patients. Our novel method of unsupervised learning could represent a reliable tool for supporting the neuropsychologists in understanding the natural structure of the cognitive performance in the neurodegenerative diseases. View Full-Text
Keywords: clustering; affinity propagation; parkinsonisms clustering; affinity propagation; parkinsonisms
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MDPI and ACS Style

Sarica, A.; Vaccaro, M.G.; Quattrone, A.; Quattrone, A. A Novel Approach for Cognitive Clustering of Parkinsonisms through Affinity Propagation. Algorithms 2021, 14, 49.

AMA Style

Sarica A, Vaccaro MG, Quattrone A, Quattrone A. A Novel Approach for Cognitive Clustering of Parkinsonisms through Affinity Propagation. Algorithms. 2021; 14(2):49.

Chicago/Turabian Style

Sarica, Alessia, Maria G. Vaccaro, Andrea Quattrone, and Aldo Quattrone. 2021. "A Novel Approach for Cognitive Clustering of Parkinsonisms through Affinity Propagation" Algorithms 14, no. 2: 49.

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