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2ARTs: A Platform for Exercise Prescriptions in Cardiac Recovery Patients

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dc.contributor.authorPereira, Andreia
dc.contributor.authorMartinho, Ricardo
dc.contributor.authorPinto, Rui
dc.contributor.authorRijo, Rui
dc.contributor.authorGrilo, Carlos
dc.date.accessioned2024-10-07T15:13:29Z
dc.date.available2024-10-07T15:13:29Z
dc.date.issued2024-03
dc.descriptionSecond International Conference on Advances in Computing Research (ACR’24)pt_PT
dc.descriptionAcknowledgments This work was financially supported by Project 2ARTS - Acesso ao Controlo Autonómico em Reabilitação Cardíaca (PDTC/EMD-EMD/6588/2020), funded by Fundação para a Ciência e a Tecnologia.pt_PT
dc.description.abstractDue to limited access, increasing costs and an ageing population, the global healthcare system faces significant coverage problems that call for innovative approaches. Health professionals are actively seeking alternative methods to provide care to an increasingly needy population, without increasing human effort and associated costs. eHealth platforms, which use technology to provide patient care, are emerging as transformative solutions for addressing these problems. This study is centered on the demand for a Decision Support System (DSS) in cardiology to enable doctors to prescribe individualized care inside Cardiac Rehabilitation Programmes (CRPs). The 2ARTs project’s main objective is to include a cardiac rehabilitation platform with a DSS within the hospital infrastructure. This DSS uses models to classify patients into different groups, delivering crucial information to assist with decisions regarding treatment. Regarding the DSS, Principal Component Analysis (PCA) emerged as a standout technique for dimensionality reduction, due to its interoperability with clustering algorithms and superior evaluation metrics. The most appropriate clustering technique was determined to be the K-means algorithm, which was supported by the experts analysis. In accordance with the goals of the 2ARTs project, this integration of PCA and K-means provides meaningful insights that improve reasoned decision-making.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationPereira, A., Martinho, R., Pinto, R., Rijo, R., Grilo, C. (2024). 2ARTs: A Platform for Exercise Prescriptions in Cardiac Recovery Patients. In: Daimi, K., Al Sadoon, A. (eds) Proceedings of the Second International Conference on Advances in Computing Research (ACR’24). ACR 2024. Lecture Notes in Networks and Systems, vol 956. Springer, Cham. https://doi.org/10.1007/978-3-031-56950-0_11pt_PT
dc.identifier.doihttps://doi.org/10.1007/978-3-031-56950-0_11pt_PT
dc.identifier.eissn978-3-031-56950-0
dc.identifier.issn978-3-031-56949-4
dc.identifier.urihttp://hdl.handle.net/10400.8/10147
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-031-56950-0_11pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectCardiac Rehabilitation Programmespt_PT
dc.subjectClustering Algorithmspt_PT
dc.subjectData Analytics in Healthcarept_PT
dc.subjectDecision Support Systempt_PT
dc.subjectMachine Learningpt_PT
dc.subjectPredictive Modelspt_PT
dc.title2ARTs: A Platform for Exercise Prescriptions in Cardiac Recovery Patientspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FEMD-EMD%2F6588%2F2020/PT
oaire.citation.endPage136pt_PT
oaire.citation.startPage125pt_PT
oaire.citation.titleProceedings of the Second International Conference on Advances in Computing Research (ACR’24)pt_PT
oaire.citation.volume956pt_PT
oaire.fundingStream3599-PPCDT
person.familyNameMartinho
person.familyNameRijo
person.familyNameGrilo
person.givenNameRicardo
person.givenNameRui
person.givenNameCarlos
person.identifier.ciencia-idF51E-9BB5-EF92
person.identifier.ciencia-id081D-025A-33BC
person.identifier.orcid0000-0003-1157-7510
person.identifier.orcid0000-0002-9348-0474
person.identifier.orcid0000-0001-9727-905X
person.identifier.ridK-8277-2013
person.identifier.ridM-9551-2013
person.identifier.scopus-author-id25823103700
person.identifier.scopus-author-id36861366200
person.identifier.scopus-author-id23466972200
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsclosedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationb2a74e46-f06c-4dcd-8c64-8f78f1d55440
relation.isAuthorOfPublicatione69d7599-392c-4f8f-a96a-bf0a0d15c8b1
relation.isAuthorOfPublicationf2075503-40b3-49da-81c3-e0c50f97c9ab
relation.isAuthorOfPublication.latestForDiscoveryb2a74e46-f06c-4dcd-8c64-8f78f1d55440
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