Department of Physiology, Medical School, National and Kapodistrian University of Athens, 75, Mikras Asias, 11527, Athens, Greece.
Assisted Conception Unit, 2nd Department of Obstetrics and Gynecology, Aretaieion Hospital, Medical School, National and Kapodistrian University of Athens, 76, Vasilisis Sofias Avenue, 11528, Athens, Greece.
J Assist Reprod Genet. 2018 Sep;35(9):1545-1557. doi: 10.1007/s10815-018-1266-6. Epub 2018 Jul 27.
Mathematics rules the world of science. Innovative technologies based on mathematics have paved the way for implementation of novel strategies in assisted reproduction. Ascertaining efficient embryo selection in order to secure optimal pregnancy rates remains the focus of the in vitro fertilization scientific community and the strongest driver behind innovative approaches. This scoping review aims to describe and analyze complex models based on mathematics for embryo selection, devices, and software most widely employed in the IVF laboratory and algorithms in the service of the cutting-edge technology of artificial intelligence. Despite their promising nature, the practicing embryologist is the one ultimately responsible for the success of the IVF laboratory and thus the one to approve embracing pioneering technologies in routine practice. Applied mathematics and computational biology have already provided significant insight into the selection of the most competent preimplantation embryo. This review describes the leap of evolution from basic mathematics to bioinformatics and investigates the possibility that computational applications may be the means to foretell a promising future for the IVF clinical practice.
数学统治着科学世界。基于数学的创新技术为在辅助生殖中实施新策略铺平了道路。确定有效的胚胎选择以确保最佳妊娠率仍然是体外受精科学界的焦点，也是创新方法的最强驱动力。本范围综述旨在描述和分析胚胎选择、在体外受精实验室中最广泛使用的设备和软件以及人工智能尖端技术服务的复杂数学模型和算法。尽管它们具有很大的发展潜力，但胚胎学家是最终负责体外受精实验室成功的人，因此也是批准将开创性技术纳入常规实践的人。应用数学和计算生物学已经为选择最有能力的胚胎提供了重要的见解。本综述描述了从基础数学到生物信息学的进化飞跃，并探讨了计算应用程序是否可能成为预测体外受精临床实践美好未来的手段。
