Proceedings of the International scientific and practical conference ―New York Global Science Conference 2026‖ (May 18-20, 2026) / Publisher website: www.naukainfo.com. – New York, USA, 2026. - 322 p.

265 selection. Hum Reprod Open. 2021;2021(4):hoab040. doi:10.1093/hropen/hoab040. 3. Liu Y, Afnan M, Conitzer V, Rudin C, Savulescu J. Embryo selection by "black-box" artificial intelligence: the ethical and epistemic considerations. Fertil Reprod. 2022;4(3):147-147. doi:10.1142/S2661318222740590. 4. Afnan MAM, Rudin C, Conitzer V, Savulescu J, Mishra A, Liu Y, et al. Ethical implementation of artificial intelligence to select embryos in in vitro fertilization. arXiv [Preprint]. 2021. Available from: arXiv:2105.00060. 5. Berntsen J, Rimestad J, Lassen JT, Tran D, Kragh MF. Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences. arXiv [Preprint]. 2021. Available from: arXiv:2103.07262. 6. Alpha Scientists in Reproductive Medicine, ESHRE Special Interest Group of Embryology. The Istanbul consensus workshop on embryo assessment: proceedings of an expert meeting. Hum Reprod. 2011;26(6):1270-1283. 7. Gardner DK, Schoolcraft WB. In vitro culture of human blastocysts. In: Jansen R, Mortimer D, editors. Towards Reproductive Certainty: Fertility and Genetics Beyond 1999. Carnforth: Parthenon Press; 1999. p. 378-388. 8. Meseguer M, Herrero J, Tejera A, Hilligsoe KM, Ramsing NB, Remohi J. The use of morphokinetics as a predictor of embryo implantation. Hum Reprod. 2011;26(10):2658-2671. 9. Ciray HN, Campbell A, Agerholm IE, Aguilar J, Chamayou S, Esbert M, et al. Proposed guidelines on the nomenclature and annotation of dynamic human embryo monitoring by a time-lapse user group. Hum Reprod. 2014;29(12):2650- 2660. 10. Dimitriadis I, Zaninovic N, Bormann CL, Veeck LL. Artificial intelligence in embryo selection: current evidence and future perspectives. J Assist Reprod Genet. 2023;40(5):1021-1032.