Feasibility of deep learning for predicting live birth from a blastocyst image in patients classified by age

PURPOSE: To identify artificial intelligence (AI) classifiers in images of blastocysts to predict the probability of achieving a live birth in patients classified by age. Results are compared to those obtained by conventional embryo (CE) evaluation. METHODS: A total of 5691 blastocysts were retrospe...

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Detalles Bibliográficos
Autores principales: Miyagi, Yasunari, Habara, Toshihiro, Hirata, Rei, Hayashi, Nobuyoshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6452012/
https://www.ncbi.nlm.nih.gov/pubmed/30996683
http://dx.doi.org/10.1002/rmb2.12266

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6452012/
https://www.ncbi.nlm.nih.gov/pubmed/30996683
http://dx.doi.org/10.1002/rmb2.12266

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