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dc.contributor.authorGarcía-Vicente, Clara
dc.contributor.authorChushig-Muzo, David
dc.contributor.authorMora-Jimenez, Inmaculada
dc.contributor.authorFabelo, Himar
dc.contributor.authorGram, Inger Torhild
dc.contributor.authorLøchen, Maja-Lisa
dc.contributor.authorGranja, Conceição
dc.contributor.authorSoguero-Ruiz, Cristina
dc.date.accessioned2024-03-27T11:07:08Z
dc.date.available2024-03-27T11:07:08Z
dc.date.created2024-01-15T12:51:40Z
dc.date.issued2023
dc.identifier.citationGarcía-Vicente, C., Chushig-Muzo, D., Mora-Jimenez, I., Fabelo, H., Gram, I. T., Løchen, M.-L., Granja, C. & Soguero-Ruiz, C. (2023). Clinical Synthetic Data Generation to Predict and Identify Risk Factors for Cardiovascular Diseases. Lecture Notes in Computer Science (LNCS). 13814. doi:en_US
dc.identifier.issn1611-3349
dc.identifier.urihttps://hdl.handle.net/11250/3124334
dc.descriptionAuthor’s accepted manuscript (postprint)
dc.descriptionThis is an Accepted Manuscript of an article published by Springer Nature in Lecture Notes in Computer Science (LNCS) on 21/01/2023
dc.descriptionAvailable online: 10.1007/978-3-0-031-23905-2_6
dc.language.isoengen_US
dc.publisherSpringer Science+Business Mediaen_US
dc.titleClinical Synthetic Data Generation to Predict and Identify Risk Factors for Cardiovascular Diseasesen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.source.pagenumber17en_US
dc.source.volume13814en_US
dc.source.journalLecture Notes in Computer Science (LNCS)en_US
dc.identifier.doi10.1007/978-3-031-23905-2_6
dc.identifier.cristin2226604


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