A novel machine-learning framework based on early embryo morphokinetics identifies a feature signature associated with blastocyst development
Abstract Background Artificial Intelligence entails the application of computer algorithms to the huge and heterogeneous amount of morphodynamic data produced by Time-Lapse Technology. In this context, Machine Learning (ML) methods were developed in order to assist embryologists with automatized and...
Main Authors: | , , , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
BMC
2024-03-01
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Series: | Journal of Ovarian Research |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13048-024-01376-6 |