Cite
Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF.
MLA
Diakiw, S. M., et al. “Development of an Artificial Intelligence Model for Predicting the Likelihood of Human Embryo Euploidy Based on Blastocyst Images from Multiple Imaging Systems during IVF.” Human Reproduction, vol. 37, no. 8, Aug. 2022, pp. 1746–59. EBSCOhost, https://doi.org/10.1093/humrep/deac131.
APA
Diakiw, S. M., Hall, J. M. M., VerMilyea, M. D., Amin, J., Aizpurua, J., Giardini, L., Briones, Y. G., Lim, A. Y. X., Dakka, M. A., Nguyen, T. V., Perugini, D., & Perugini, M. (2022). Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF. Human Reproduction, 37(8), 1746–1759. https://doi.org/10.1093/humrep/deac131
Chicago
Diakiw, S M, J M M Hall, M D VerMilyea, J Amin, J Aizpurua, L Giardini, Y G Briones, et al. 2022. “Development of an Artificial Intelligence Model for Predicting the Likelihood of Human Embryo Euploidy Based on Blastocyst Images from Multiple Imaging Systems during IVF.” Human Reproduction 37 (8): 1746–59. doi:10.1093/humrep/deac131.