End-to-end deep learning for recognition of ploidy status using time-lapse videos

PURPOSE: Our retrospective study is to investigate an end-to-end deep learning model in identifying ploidy status through raw time-lapse video. METHODS: By randomly dividing the dataset of time-lapse videos with known outcome of preimplantation genetic testing for aneuploidy (PGT-A), a deep learning...

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Detalles Bibliográficos
Publicado en:J Assist Reprod Genet
Main Authors: Lee, Chun-I, Su, Yan-Ru, Chen, Chien-Hong, Chang, T. Arthur, Kuo, Esther En-Shu, Zheng, Wei-Lin, Hsieh, Wen-Ting, Huang, Chun-Chia, Lee, Maw-Sheng, Liu, Mark
Formato: Artigo
Idioma:Inglês
Publicado: Springer US 2021
Assuntos:
Assisted Reproduction Technologies
Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC8324635/
https://ncbi.nlm.nih.gov/pubmed/34021832
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10815-021-02228-8
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