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Clinical prediction and spatial statistical analysis of ascending thoracic aortic aneurysm structure

datacite.subject.fosCiências Naturais::Matemáticas
dc.contributor.authorRodriguez, Katalina
dc.contributor.authorCarvalho, Alda
dc.contributor.authorValente, Rodrigo
dc.contributor.authorXavier, José
dc.contributor.authorTomás, António
dc.date.accessioned2026-02-02T13:59:22Z
dc.date.available2026-02-02T13:59:22Z
dc.date.issued2026-01-09
dc.description.abstractThis study presents an analysis of data from patients with ascending thoracic aortic aneurysms (ATAAs). Two databases of 87 patients were available: one containing clinical variables and the other consisting of measurements of the maximum diameter taken along the ascending aorta. For the clinical database, both a supervised and an unsupervised learning method were applied to explore patterns within the data. On the other hand, for the ascending aorta dataset, experimental variograms were calculated, from which key parameters of interest were extracted. These parameters were then analyzed over time to assess temporal patterns. This analysis aimed to assess the emergence of similar patterns or behaviour in patients with aneurysms of comparable sizes. Based on the analyses conducted, the clinical variables with the greatest importance in surgical decision-making were identified, while the spatial statistical analysis revealed patterns that may be related to elasticity, stiffness, or deformations of the aortaeng
dc.description.sponsorshipThis research was funded by the Portuguese Foundation for Science and Technology (FCT, IP) under the projects “Fluid–structure interaction for functional assessment of ascending aortic aneurysms: a biomechanical-based approach towards clinical practice” (AneurysmTool) DOI: 10.54499/PTDC/EMD-EMD/1230/2021; UID/00667: Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e Industrial (UNIDEMI); R. Valente Ph.D. grant 2022.12223.BD. A. Carvalho was partially supported by national funds through FCT- Fundação para a Ciência e a Tecnologia, I.P., in the framework of the unit ISEG Research; UID/06522/2025. A. C. Tomás was supported by Projetos de Investigação Clínica CUF Academic Center 2024.
dc.identifier.citationOviedo Rodríguez, K., Carvalho, A., Valente, R., Xavier, J., & Tomás, A. C. (2026). Clinical Prediction and Spatial Statistical Analysis of Ascending Thoracic Aortic Aneurysm Structure. Mathematical and Computational Applications, 31(1), 10. https://doi.org/10.3390/mca31010010
dc.identifier.doi10.3390/mca31010010
dc.identifier.urihttp://hdl.handle.net/10400.2/21118
dc.language.isoeng
dc.peerreviewedyes
dc.publisherMDPI
dc.relationFluid-structure interaction for functional assessment of ascending aortic aneurysms: a biomechanical-based approach toward clinical practice
dc.relationISEG Research in Economics and Management
dc.relation.hasversionhttps://www.mdpi.com/2297-8747/31/1/10
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAscending aortic aneurysm
dc.subjectSupervised and unsupervised methods
dc.subjectSpatial statistics
dc.subjectVariogram
dc.titleClinical prediction and spatial statistical analysis of ascending thoracic aortic aneurysm structureeng
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleFluid-structure interaction for functional assessment of ascending aortic aneurysms: a biomechanical-based approach toward clinical practice
oaire.awardTitleISEG Research in Economics and Management
oaire.awardURIhttp://hdl.handle.net/10400.2/21116
oaire.awardURIhttp://hdl.handle.net/10400.2/21117
oaire.fundingStreamConcurso de Projetos IC&DT em Todos os Domínios Científicos
oaire.fundingStreamAvaliação UID 2023/2024 PRR
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameCarvalho
person.givenNameAlda
person.identifierAAA-4372-2021
person.identifier.ciencia-idFD18-CBDD-B7C7
person.identifier.orcid0000-0003-2642-4947
person.identifier.scopus-author-id25027091800
relation.isAuthorOfPublicationcb806308-9989-403b-97b7-42d77143f6d5
relation.isAuthorOfPublication.latestForDiscoverycb806308-9989-403b-97b7-42d77143f6d5
relation.isProjectOfPublication362e6f1d-9046-4b5b-9338-64c7854b912b
relation.isProjectOfPublication1c27ad4c-fec3-4ae9-a67b-29c84c96e835
relation.isProjectOfPublication.latestForDiscovery362e6f1d-9046-4b5b-9338-64c7854b912b

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