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通过人工智能选择胚胎与胚胎学家:一个系统的审查.

M Salih1,2, C Austin1,2, R R Warty1

  • 1Department of Obstetrics and Gynaecology, Monash University, Clayton, Victoria, Australia.

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概括
此摘要是机器生成的。

人工智能 (AI) 在体外受精 (IVF) 胚胎选择精度方面显著超过胚胎学家. 人工智能模型在预测胚胎形态和临床怀孕结果方面显示出更高的可靠性,有可能提高试管婴儿成功率.

关键词:
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科学领域:

  • 生殖医学 生殖医学
  • 医疗保健中的人工智能
  • 胚胎学 胚胎学

背景情况:

  • 试管婴儿 (IVF) 的成功率仍然低于最佳水平,特别是随着女性年龄的增加.
  • 人工智能 (AI) 提供了提高胚胎选择客观性的潜力,这是一个传统上受人类主观性限制的过程.
  • 审查人工智能在胚胎选择中的表现与胚胎学家相比,对于改善试管婴儿结果至关重要.

研究的目的:

  • 将人工智能 (AI) 决策支持系统与人类胚胎学家在胚胎选择中的性能进行比较.
  • 评估AI在预测胚胎形态和试管婴儿治疗中的临床结果方面的准确性.

主要方法:

  • 从2005年到2022年,在主要的科学数据库 (PubMed,EMBASE,Ovid Medline,IEEE Xplore) 中进行了全面的文献搜索.
  • 包括专注于人工智能在试管婴儿中的应用,评估胚胎评估的准确性,敏感性和特异性以及临床结果预测的研究.
  • 偏差风险使用修改后的下方和黑色检查列表进行评估.

主要成果:

  • 人工智能模型在预测胚胎形态 (中位数为75.5%对65.4%) 和临床怀孕 (中位数为77.8%对64%) 方面比胚胎学家更准确.
  • 在结合图像/时间延迟和临床数据时,人工智能达到81.5%的中位精度,明显超过胚胎学家 (51%).
  • 人工智能在预测胚胎质量和试管婴儿成功方面始终表现出更高的可靠性和准确性.

结论:

  • 人工智能在IVF中改善胚胎选择方面显示出显著的希望,在评估的研究中始终超过临床团队.
  • 需要进一步的研究,以便在临床环境中对人工智能进行前性评估,并通过外部验证解决模型通用性的问题.
  • 建议将重点转向活产作为主要的临床结果,并使用多样化的,经过验证的数据库来开发IVF中的AI.