Pang Jiyun, Hou Wei, Nong Yuxiang, Bian Ang, Xu Wenming
（ 610041） West China School of Medicine, Sichuan University, Chengdu 610041, China.
Sichuan Da Xue Xue Bao Yi Xue Ban. 2024 Sep 20;55(5):1322-1328. doi: 10.12182/20240960603.
Infertility is a global health issue, and more and more people are hoping to have babies by means of assisted reproductive technology. However, there are still many challenges in fertilization and pregnancy outcomes. Sperm quality is a key factor affecting the success rate of assisted reproduction. Therefore, sperm quality screening is crucial for achieving breakthroughs in assisted reproduction technology. At present, with its capabilities in the field of image recognition, artificial intelligence (AI) is providing new ideas and methods for sperm screening. Various attempts have been made with AI-based models to evaluate indicators such as sperm morphology, DNA quality, and motility level, and some results have been achieved. Herein, we reviewed the application of AI in sperm quality analysis and selection, providing support for the future development of AI and the improvement in the fertilization rate and outcomes of assisted reproductive technology.
不孕症是一个全球性的健康问题，越来越多的人希望通过辅助生殖技术来生育。然而，在受精和妊娠结局方面仍存在许多挑战。精子质量是影响辅助生殖成功率的关键因素。因此，精子质量筛查对于辅助生殖技术取得突破至关重要。目前，人工智能（AI）凭借其在图像识别领域的能力，正在为精子筛查提供新的思路和方法。基于AI的模型已进行了各种尝试，以评估精子形态、DNA质量和活力水平等指标，并取得了一些成果。在此，我们综述了AI在精子质量分析与筛选中的应用，为AI的未来发展以及辅助生殖技术受精率和结局的改善提供支持。
