[iDAScore (智能数据分析得分) 在常规试管婴儿实验室实践中对胚胎选择的兴趣:初步研究结果]
S Sarandi1, Y Boumerdassi2, L O'Neill1
1Service d'histologie-embryologie-cytogénétique-CECOS, centre hospitalier universitaire Jean-Verdier, AP-HP, avenue du 14-Juillet, 93140 Bondy, France.
Gynecologie, obstetrique, fertilite & senologie
|June 4, 2023
概括
像iDAScore这样的人工智能 (AI) 模型可以可靠地对胚胎细胞进行分类,以改善试管婴儿的结果. 这种人工智能工具标准化了胚胎选择,识别出那些植入潜力最高的胚胎,以提高妊娠率.
科学领域:
- 辅助生殖技术 (ART) 是一种辅助生殖技术.
- 胚胎学 胚胎学
- 人工智能在医学中的应用
背景情况:
- 胚胎选择在ART中对于成功的试管婴儿至关重要.
- 优化胚胎选择可以改善临床结果.
- 人工智能模型为标准化胚胎评估提供了潜力.
研究的目的:
- 将人工智能驱动的胚胎选择 (iDAScore) 与胚胎学家的专业知识进行比较.
- 评估iDAScore在胚胎细胞质量分类中的可靠性.
- 评估AI预测胚胎植入潜力的能力.
主要方法:
- 对iDAScore v1.0和胚胎学家分类的比较分析.
- 311个D5胚胎囊按质量分类 (顶级,好,差).
- 对151个胚胎囊的植入数据的分析.
主要成果:
- 在胚囊细胞分类方面,iDAScore和胚胎学家之间的显著一致.
- 根据iDAScore的数据,发现了具有更高植入率的囊胞.
- 人工智能证明了可靠的层次性胚胎细胞分类.
结论:
- iDAScore提供可复制和可靠的胚胎囊分类.
- 人工智能工具可以识别具有最高植入潜力的胚胎.
- 人工智能有可能通过标准化选择彻底改变试管婴儿实验室实践.
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