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人工智能在辅助生殖技术中的应用:精子筛选、胚胎发育潜能及妊娠预测的前景

The Application of Artificial Intelligence in Assisted Reproductive Technology:Prospects for Sperm Screening,Embryo Developmental Potential and Pregnancy Prediction

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【作者】 张武文; 简献忠; 李凯; 尹萍; 严骅;

【Author】 ZHANG Wuwen;JIAN Xianzhong;LI Kai;YIN Ping;YAN Hua;Department of Infertility and Reproductive Medicine, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine;School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology;

【通讯作者】 张武文;严骅;

【机构】 上海中医药大学附属曙光医院,不孕不育与生殖医学科; 上海理工大学,光电信息与计算机工程学院;

【摘要】 随着人工智能(artificial intelligence, AI)技术的迅速发展,其在辅助生殖领域的应用越来越受到关注。辅助生殖技术在帮助不孕不育夫妇实现生育愿望方面发挥了重要作用,而AI技术的引入为提高胚胎选择效率和妊娠成功率提供了新的可能性。越来越多的研究表明, AI技术在精子筛选、胚胎发育潜能评估和妊娠预测中的应用不断增加,特别是在胚胎图像分析、数据挖掘和预测模型构建等方面展现出了显著的优势。尽管AI技术潜力巨大,但其实际应用仍面临数据质量、算法透明性和伦理问题等挑战。该文旨在综述AI技术在辅助生殖中的最新研究进展。该文将探讨其在精子筛选、胚胎选择和妊娠预测中的应用效果,并提出未来研究的方向,以为临床实践提供参考,从而促进AI技术在辅助生殖领域的进一步应用。

【Abstract】 With the rapid development of AI(artificial intelligence) technology, its application in the field of assisted reproduction has received increasing attention. Assisted reproductive technology plays an important role in helping infertile couples realize their fertility wishes, and the introduction of AI technology offers new possibilities for improving the efficiency of embryo selection and pregnancy success rates. More and more studies have shown that the application of AI technology in sperm screening, embryo developmental potential assessment and pregnancy prediction is gradually increasing, especially in embryo image analysis, data mining and prediction model construction, showing significant advantages. Despite the great potential of AI technology, its practical application still faces challenges such as data quality, algorithm transparency and ethical issues. The aim of this paper is to review the latest research progress of AI technology in assisted reproduction. This article will explore the effects of its application in sperm screening, embryo selection and pregnancy prediction, and propose directions for future research to provide references for clinical practice, thereby promoting the further application of AI technology in assisted reproduction.

【基金】 国家自然科学基金面上基金(批准号:81571442)资助的课题~~
  • 【文献出处】 中国细胞生物学学报 ,Chinese Journal of Cell Biology , 编辑部邮箱 ,2024年12期
  • 【分类号】R714.8
  • 【下载频次】95
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