{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T10:05:53Z","timestamp":1783159553809,"version":"3.54.6"},"reference-count":64,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,11,2]],"date-time":"2023-11-02T00:00:00Z","timestamp":1698883200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Graph neural networks (GNNs) have been increasingly employed in the field of Parkinson\u2019s disease (PD) research. The use of GNNs provides a promising approach to address the complex relationship between various clinical and non-clinical factors that contribute to the progression of PD. This review paper aims to provide a comprehensive overview of the state-of-the-art research that is using GNNs for PD. It presents PD and the motivation behind using GNNs in this field. Background knowledge on the topic is also presented. Our research methodology is based on PRISMA, presenting a comprehensive overview of the current solutions using GNNs for PD, including the various types of GNNs employed and the results obtained. In addition, we discuss open issues and challenges that highlight the limitations of current GNN-based approaches and identify potential paths for future research. Finally, a new approach proposed in this paper presents the integration of new tasks for the engineering of GNNs for PD monitoring and alert solutions.<\/jats:p>","DOI":"10.3390\/s23218936","type":"journal-article","created":{"date-parts":[[2023,11,2]],"date-time":"2023-11-02T09:28:13Z","timestamp":1698917293000},"page":"8936","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Graph Neural Networks for Parkinson\u2019s Disease Monitoring and Alerting"],"prefix":"10.3390","volume":"23","author":[{"given":"Nikolaos","family":"Zafeiropoulos","sequence":"first","affiliation":[{"name":"Intelligent Systems Laboratory, Department of Cultural Technology and Communication, University of the Aegean, 81100 Mytilene, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0548-6268","authenticated-orcid":false,"given":"Pavlos","family":"Bitilis","sequence":"additional","affiliation":[{"name":"Intelligent Systems Laboratory, Department of Cultural Technology and Communication, University of the Aegean, 81100 Mytilene, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7006-1536","authenticated-orcid":false,"given":"George E.","family":"Tsekouras","sequence":"additional","affiliation":[{"name":"Intelligent Systems Laboratory, Department of Cultural Technology and Communication, University of the Aegean, 81100 Mytilene, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7838-9691","authenticated-orcid":false,"given":"Konstantinos","family":"Kotis","sequence":"additional","affiliation":[{"name":"Intelligent Systems Laboratory, Department of Cultural Technology and Communication, University of the Aegean, 81100 Mytilene, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Dar, M.N., Akram, M.U., Yuvaraj, R., Khawaja, S.G., and Murugappan, M. 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