Abstract：
The integration of artificial intelligence (AI) and deep learning algorithms into medical care has been the focus of development over the last decade, particularly in the field of assisted reproductive technologies and in vitro fertilization (IVF). With embryo morphology the cornerstone of clinical decision making for IVF, the field of IVF is highly reliant on visual assessments that can be prone to error and subjectivity and be dependent on the level of training and expertise of the observing embryologist. Implementing AI algorithms into the IVF laboratory allows for reliable, objective, and timely assessments of both clinical parameters and microscopy images. This review discusses the ever-expanding applications of AI algorithms within the IVF embryology laboratory, aiming to discuss the many advances in multiple aspects of the IVF process. We will discuss how AI will improve various processes and procedures such as assessing oocyte quality, sperm selection, fertilization assessment, embryo assessment, ploidy prediction, embryo transfer selection, cell tracking, embryo witnessing, micromanipulation, and quality management. Overall, AI provides great potential and promise to improve not only clinical outcomes but also laboratory efficiency, a key focus because IVF clinical volume continues to increase nationwide.
摘要：
人工智能（AI）和深度学习算法在医疗保健中的集成一直是过去十年的发展重点。特别是在辅助生殖技术和体外受精（IVF）领域。胚胎形态学是IVF临床决策的基石，IVF领域高度依赖于视觉评估,视觉评估可能容易出错和主观性,并且依赖于观察胚胎学家的培训水平和专业知识.在IVF实验室中实施AI算法可以实现可靠，目标,并及时评估临床参数和显微镜图像。这篇综述讨论了人工智能算法在IVF胚胎学实验室中不断扩大的应用，旨在讨论试管婴儿过程多个方面的许多进展。我们将讨论AI将如何改进各种过程和程序，例如评估卵母细胞质量，精子选择,施肥评估，胚胎评估,倍性预测，胚胎移植选择，细胞追踪,胚胎见证，显微操作,和质量管理。总的来说,人工智能提供了巨大的潜力和希望，不仅可以改善临床结果，还可以改善实验室效率。这是一个重点，因为全国IVF临床量持续增加。
