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在当代生殖医学中,人类仍然不可或缺。

In Contemporary Reproductive Medicine Human Beings are Not Yet Dispensable.

作者信息

Allahbadia Gautam N, Allahbadia Swati G, Gupta Akanksha

机构信息

MMC IVF, Dubai, UAE.

Rotunda-Center for Human Reproduction, Mumbai, India.

出版信息

J Obstet Gynaecol India. 2023 Aug;73(4):295-300. doi: 10.1007/s13224-023-01747-x. Epub 2023 Apr 3.

Abstract

In the past few years almost every aspect of an IVF cycle has been investigated, including research on sperm, color doppler in follicular studies, prediction of embryo cleavage, prediction of blastocyst formation, scoring blastocyst quality, prediction of euploid blastocysts and live birth from blastocysts, improving the embryo selection process, and for developing deep machine learning (ML) algorithms for optimal IVF stimulation protocols. Also, artificial intelligence (AI)-based methods have been implemented for some clinical aspects of IVF, such as assessing patient reproductive potential and individualizing gonadotropin stimulation protocols. As AI has the inherent capacity to analyze "Big" data, the goal will be to apply AI tools to the analysis of all embryological, clinical, and genetic data to provide patient-tailored individualized treatments. Human skillsets including hand eye coordination to perform an embryo transfer is probably the only step of IVF that is outside the realm of AI & ML today. Embryo transfer success is presently human skill dependent and deep machine learning may one day intrude into this sacred space with the advent of programed humanoid robots. Embryo transfer is arguably the rate limiting step in the sequential events that complete an IVF cycle. Many variables play a role in the success of embryo transfer, including catheter type, atraumatic technique, and the use of sonography guidance before and during the procedure of embryo transfer. In contemporary Reproductive Medicine human beings are not yet dispensable.

摘要

在过去几年里,体外受精(IVF)周期的几乎每个方面都得到了研究,包括精子研究、卵泡研究中的彩色多普勒、胚胎分裂预测、囊胚形成预测、囊胚质量评分、整倍体囊胚预测以及囊胚活产预测、改进胚胎选择过程,以及开发用于优化IVF刺激方案的深度机器学习(ML)算法。此外,基于人工智能(AI)的方法已应用于IVF的一些临床方面,如评估患者的生殖潜力和个性化促性腺激素刺激方案。由于AI具有分析“大数据”的内在能力,目标将是应用AI工具分析所有胚胎学、临床和遗传数据,以提供针对患者的个性化治疗。包括进行胚胎移植所需的手眼协调能力在内的人类技能集,可能是目前IVF过程中唯一不属于AI和ML范畴的步骤。目前,胚胎移植的成功取决于人类技能,随着程序化人形机器人的出现,深度机器学习可能有一天会进入这个神圣的领域。胚胎移植可以说是完成IVF周期的一系列事件中的限速步骤。许多变量对胚胎移植的成功起着作用,包括导管类型、无创技术以及胚胎移植过程中及之前超声引导的使用。在当代生殖医学中,人类仍然不可或缺。

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In Contemporary Reproductive Medicine Human Beings are Not Yet Dispensable.在当代生殖医学中,人类仍然不可或缺。
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