Mining of variables from embryo morphokinetics, blastocyst’s morphology and patient parameters: An approach to predict the live birth in the assisted reproduction service

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorChéles, Dóris Spinosa [UNESP]-
Autor(es): dc.creatorDal Molin, Eloiza Adriane [UNESP]-
Autor(es): dc.creatorRocha, José Celso [UNESP]-
Autor(es): dc.creatorNogueira, Marcelo Fábio Gouveia [UNESP]-
Data de aceite: dc.date.accessioned2022-02-22T00:47:40Z-
Data de disponibilização: dc.date.available2022-02-22T00:47:40Z-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.5935/1518-0557.20200014-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/206625-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/206625-
Descrição: dc.descriptionBased on growing demand for assisted reproduction technology, improved predictive models are required to optimize in vitro fertilization/intracytoplasmatic sperm injection strategies, prioritizing single embryo transfer. There are still several obstacles to overcome for the purpose of improving assisted reproductive success, such as intra-and inter-observer subjectivity in embryonic selection, high occurrence of multiple pregnancies, maternal and neonatal complications. Here, we compare studies that used several variables that impact the success of assisted reproduction, such as blastocyst morphology and morphokinetic aspects of embryo development as well as characteristics of the patients submitted to assisted reproduction, in order to predict embryo quality, implantation or live birth. Thereby, we emphasize the proposal of an artificial intelligence-based platform for a more objective method to predict live birth.-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionUniversidade Estadual Paulista-
Descrição: dc.descriptionLaboratório de Matemática Aplicada Department of Biological Sciences School of Languages and Sciences São Paulo State University (UNESP), Campus Assis-
Descrição: dc.descriptionLaboratório de Micromanipulação Embrionária Department of Biological Sciences School of Sciences and Languages São Paulo State University (UNESP), Campus Assis-
Descrição: dc.descriptionLaboratório de Matemática Aplicada Department of Biological Sciences School of Languages and Sciences São Paulo State University (UNESP), Campus Assis-
Descrição: dc.descriptionLaboratório de Micromanipulação Embrionária Department of Biological Sciences School of Sciences and Languages São Paulo State University (UNESP), Campus Assis-
Descrição: dc.descriptionFAPESP: #2012/50533-2-
Descrição: dc.descriptionFAPESP: #2017/19323-5-
Descrição: dc.descriptionFAPESP: #2018/190530-
Descrição: dc.descriptionUniversidade Estadual Paulista: #47956-
Formato: dc.format470-479-
Idioma: dc.languageen-
Relação: dc.relationJornal Brasileiro de Reproducao Assistida-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectArtificial intelligence-
Palavras-chave: dc.subjectAssisted reproductive technology-
Palavras-chave: dc.subjectLive birth prediction-
Título: dc.titleMining of variables from embryo morphokinetics, blastocyst’s morphology and patient parameters: An approach to predict the live birth in the assisted reproduction service-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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