An artificial intelligence algorithm for automated blastocyst morphometric parameters demonstrates a positive association with implantation potential.

MLA

Fruchter-Goldmeier, Yael, et al. “An Artificial Intelligence Algorithm for Automated Blastocyst Morphometric Parameters Demonstrates a Positive Association with Implantation Potential.” Scientific Reports, vol. 13, no. 1, Sept. 2023, p. 14617. EBSCOhost, https://doi.org/10.1038/s41598-023-40923-x.

APA

Fruchter-Goldmeier, Y., Kantor, B., Ben-Meir, A., Wainstock, T., Erlich, I., Levitas, E., Shufaro, Y., Sapir, O., & Har-Vardi, I. (2023). An artificial intelligence algorithm for automated blastocyst morphometric parameters demonstrates a positive association with implantation potential. Scientific Reports, 13(1), 14617. https://doi.org/10.1038/s41598-023-40923-x

Chicago

Fruchter-Goldmeier, Yael, Ben Kantor, Assaf Ben-Meir, Tamar Wainstock, Itay Erlich, Eliahu Levitas, Yoel Shufaro, Onit Sapir, and Iris Har-Vardi. 2023. “An Artificial Intelligence Algorithm for Automated Blastocyst Morphometric Parameters Demonstrates a Positive Association with Implantation Potential.” Scientific Reports 13 (1): 14617. doi:10.1038/s41598-023-40923-x.