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Deep learning-based algorithm for predicting the live birth potential of mouse embryos
View ORCID ProfileYuta Tokuoka, View ORCID ProfileTakahiro G. Yamada, View ORCID ProfileDaisuke Mashiko, Zenki Ikeda, View ORCID ProfileTetsuya J. Kobayashi, View ORCID ProfileKazuo Yamagata, View ORCID ProfileAkira Funahashi
doi: https://doi.org/10.1101/2021.08.19.456065
Yuta Tokuoka
1Center for Biosciences and Informatics, Graduate School of Fundamental Science and Technology, Keio University, Kanagawa, Japan
Takahiro G. Yamada
1Center for Biosciences and Informatics, Graduate School of Fundamental Science and Technology, Keio University, Kanagawa, Japan
2Department of Biosciences and Informatics, Keio University, Kanagawa, Japan
Daisuke Mashiko
3Faculty of Biology-Oriented Science and Technology, Kindai University, Wakayama, Japan
Zenki Ikeda
3Faculty of Biology-Oriented Science and Technology, Kindai University, Wakayama, Japan
Tetsuya J. Kobayashi
4Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
Kazuo Yamagata
3Faculty of Biology-Oriented Science and Technology, Kindai University, Wakayama, Japan
Akira Funahashi
1Center for Biosciences and Informatics, Graduate School of Fundamental Science and Technology, Keio University, Kanagawa, Japan
2Department of Biosciences and Informatics, Keio University, Kanagawa, Japan

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Posted August 19, 2021.
Deep learning-based algorithm for predicting the live birth potential of mouse embryos
Yuta Tokuoka, Takahiro G. Yamada, Daisuke Mashiko, Zenki Ikeda, Tetsuya J. Kobayashi, Kazuo Yamagata, Akira Funahashi
bioRxiv 2021.08.19.456065; doi: https://doi.org/10.1101/2021.08.19.456065
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