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Voice analysis in Parkinson's disease

2025-05Recensão Acesso aberto
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dc.contributor.authorXavier, Daniela
dc.contributor.authorFelizardo, Virginie
dc.contributor.authorFerreira, Beatriz
dc.contributor.authorZacarias, Henriques
dc.contributor.authorPourvahab, Mehran
dc.contributor.authorSouza-Pereira, Leonice
dc.contributor.authorGarcia, Nuno M.
dc.contributor.institutionNOVALincs
dc.contributor.pblElsevier Science B.V., Amsterdam.
dc.date.accessioned2025-09-22T21:54:13Z
dc.date.available2025-09-22T21:54:13Z
dc.date.issued2025-05
dc.descriptionFunding Information: This work was partially funded by FCT/MCTES through national funds and co-funded by the FEDER–PT2020 partnership agreement under the project UIDB/50008/2020 of Instituto de Telecomunicações. This article is based on work from COST Action IC1303–AAPELEArchitectures, Algorithms and Protocols for Enhanced Living Environments and COST Action CA16226–SHELD-ON–Indoor living space improvement: Smart Habitat for the Elderly, supported by COST (European Cooperation in Science and Technology). Publisher Copyright: © 2025 The Authors
dc.description.abstractBackground and aim: Parkinson's disease is a neurodegenerative disease. It is often diagnosed at an advanced stage, which can influence the control over the illness. Therefore, the possibility of diagnosing Parkinson's disease at an earlier stage, and possibly prognosticate it, could be an advantage. Given this, a literature review that covers current studies in the field is relevant. Methods: The aim of this study is to present a systematic literature review in which the models used for the diagnosis and prognosis of Parkinson's disease through voice and speech assessment are elucidated. Three databases were consulted to obtain the studies between 2019 and 2023: SienceDirect, IEEE Xplore and ACM Library. Results: One hundred and six studies were considered eligible, considering the definition of inclusion and exclusion criteria. The vast majority of these studies (94.34%) focus on diagnosing the disease, while the remainder (11.32%) focus on prognosis. Conclusion: Voice analysis for the diagnosis and prognosis of Parkinson's disease using machine learning techniques can be achieved, with very satisfactory performance results, like is demonstrated in this systematic literature review.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent16
dc.format.extent2073037
dc.identifier.doi10.1016/j.artmed.2025.103109
dc.identifier.issn0933-3657
dc.identifier.otherPURE: 129949507
dc.identifier.otherPURE UUID: 37434f62-d53d-450a-bfed-6929047c8a80
dc.identifier.otherScopus: 105000670927
dc.identifier.otherPubMed: 40132400
dc.identifier.urihttp://hdl.handle.net/10362/188438
dc.identifier.urlhttps://www.scopus.com/pages/publications/105000670927
dc.language.isoeng
dc.peerreviewedyes
dc.relationinfo:eu-repo/grantAgreement/FCT/Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017%2F2018) - Financiamento Base/UIDB%2F50008%2F2020/PT
dc.subjectDiagnosis or prognosis
dc.subjectMachine learning
dc.subjectParkinson's disease
dc.subjectVoice or speech
dc.subjectMedicine (miscellaneous)
dc.subjectArtificial Intelligence
dc.titleVoice analysis in Parkinson's diseaseen
dc.title.subtitlea systematic literature reviewen
dc.typereview
degois.publication.titleArtificial Intelligence In Medicine
degois.publication.volume163
dspace.entity.typePublication
oaire.awardNumberUIDB/50008/2020
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017%2F2018) - Financiamento Base/UIDB%2F50008%2F2020/PT
oaire.fundingStreamConcurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017/2018) - Financiamento Base
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccess
relation.isProjectOfPublicationada2f8e7-fadc-471b-b1a7-b1e35cba8ebc
relation.isProjectOfPublication.latestForDiscoveryada2f8e7-fadc-471b-b1a7-b1e35cba8ebc

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