Performance of a deep learning based neural network in the selection of human blastocysts for implantation

Performance of a deep learning based neural network in the selection of human blastocysts for implantation

Deep learning in in vitro fertilization is currently being evaluated in the development of assistive tools for the determination of transfer order and implantation potential using time-lapse data collected through expensive imaging hardware. Assistive tools and algorithms that can work with static i...

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Bibliographic Details
Main Authors: Charles L Bormann, Manoj Kumar Kanakasabapathy, Prudhvi Thirumalaraju, Raghav Gupta, Rohan Pooniwala, Hemanth Kandula, Eduardo Hariton, Irene Souter, Irene Dimitriadis, Leslie B Ramirez, Carol L Curchoe, Jason Swain, Lynn M Boehnlein, Hadi Shafiee
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2020-09-01
Series:eLife
Subjects:
convolutional neural networks
blastocysts
human embryos
embryology
in - vitro fertilization
euploid embryos
Online Access:https://elifesciences.org/articles/55301

Internet

https://elifesciences.org/articles/55301

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