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Exploring non-invasive methods to predict Ploidy Status: Combination of blastocyst morphology image analysis and proteomic profiles by using Artificial Neural Networks

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dc.contributor.authorGarg, A.
dc.contributor.authorBari, L.
dc.contributor.authorValera, M. A.
dc.contributor.authorFernandez, E. I. [UNESP]
dc.contributor.authorRocha, J. C. [UNESP]
dc.contributor.authorQuinonero, A.
dc.contributor.authorDominguez, F.
dc.contributor.authorMeseguer, M.
dc.contributor.institutionIVIRMA
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionIVIRMA Fdn
dc.date.accessioned2022-04-28T17:20:22Z
dc.date.available2022-04-28T17:20:22Z
dc.date.issued2021-07-01
dc.description.affiliationIVIRMA, Res Lab, Valencia, Spain
dc.description.affiliationUniv Estadual Paulista UNESP, Fac Ciencias & Letras, Campus Assis, Sao Paulo, Brazil
dc.description.affiliationIVIRMA Fdn, Innovat, Valencia, Spain
dc.description.affiliationIVIRMA, IVF Lab, Valencia, Spain
dc.description.affiliationUnespUniv Estadual Paulista UNESP, Fac Ciencias & Letras, Campus Assis, Sao Paulo, Brazil
dc.format.extent52-52
dc.identifier.citationHuman Reproduction. Oxford: Oxford Univ Press, v. 36, p. 52-52, 2021.
dc.identifier.issn0268-1161
dc.identifier.urihttp://hdl.handle.net/11449/218305
dc.identifier.wosWOS:000672766500106
dc.language.isoeng
dc.publisherOxford Univ Press
dc.relation.ispartofHuman Reproduction
dc.sourceWeb of Science
dc.titleExploring non-invasive methods to predict Ploidy Status: Combination of blastocyst morphology image analysis and proteomic profiles by using Artificial Neural Networksen
dc.typeResumopt
dcterms.licensehttp://www.oxfordjournals.org/access_purchase/self-archiving_policyb.html
dcterms.rightsHolderOxford Univ Press
dspace.entity.typePublication
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Ciências e Letras, Assispt

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