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人工智能释放了卵细胞能力:MAGENTATM的表现优于临床预测器,并提高了euploidy建模
Amanda Setti1, Daniela Braga2, Maite Del Collado2
1Sapientiae Institute - Centro de Estudos e Pesquisa em Reprodução Humana Assistida, São Paulo - SP, Brazil.
F&S science
|March 13, 2026
概括
由人工智能衍生的卵细胞形态评分 (MAGENTATM) 显示了与受精,胚胎发育和euploidy的独立关联. 将MAGENTATM与临床和胚胎学数据相结合,显著提高了对胚胎繁衍的预测准确性.
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:
- 卵细胞形态对于试管婴儿的成功至关重要.
- 在辅助生殖技术中,预测胚胎欧化仍然是一个挑战.
- 人工智能为客观形态评估提供了新的工具.
研究的目的:
- 评估AI衍生MAGENTATM得分对卵细胞和胚胎结果的预测能力.
- 为了确定MAGENTATM是否会在与其他变量相结合时改善euploidy预测模型.
- 为了确定影响MAGENTATM分数的因素.
主要方法:
- 对2196名接受ICSI的患者进行了回顾性队列研究.
- 在ICSI之前使用MAGENTATM得分的13370个卵细胞的分析.
- 开发和评估使用ROC分析和SHAP值进行euploidy的预测模型 (仅MAGENTA,MAGENTATM +形态,完整模型).
主要成果:
- MAGENTATM得分与受精,爆发和euploidy (p < 0.001) 有正相关性.
- 女性年龄是MAGENTATM最强的负预测因素 (B = -0.063/年;p < 0.001).
- 整合MAGENTATM,胚胎形态和临床数据的完整模型实现了最高的euploidy预测准确性 (AUC 0.666).
结论:
- MAGENTATM是关键IVF结果的独立预测器,包括胚胎euploidy.
- 将MAGENTATM与胚胎形态学和临床数据相结合,显著提高了euploidy预测性能.
- 人工智能驱动的卵细胞评估有望提高试管婴儿成功率.
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