在当代的生殖医学中,人类还不是不可用的
Gautam N Allahbadia1,2, Swati G Allahbadia2, Akanksha Gupta3
1MMC IVF, Dubai, UAE.
Journal of obstetrics and gynaecology of India
|September 13, 2023
概括
人工智能 (AI) 和机器学习 (ML) 正通过个性化治疗来彻底改变体外受精 (IVF). 虽然人工智能优化了许多试管婴儿的步骤,但胚胎移植仍然取决于人类,突出了目前的局限性.
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:
- 试管婴儿 (IVF) 周期涉及许多变量,从精子分析到胚胎选择和刺激协议.
- 最近的进展集中在深度机器学习 (ML) 和人工智能 (AI) 上,以优化试管婴儿过程并预测结果.
- 人工智能分析大数据集的能力为试管婴儿中个性化患者治疗提供了潜力.
研究的目的:
- 探索AI和ML在优化试管婴儿周期各个阶段的当前和潜在应用.
- 确定试管婴儿的各个方面仍然超出了当前AI和ML能力的范围.
- 讨论人类专业知识在试管婴儿中的作用,特别是在胚胎移植程序中.
主要方法:
- 审查当前的研究和AI和ML在IVF中的应用.
- 从试管婴儿的胚胎学,临床和遗传方面的数据分析.
- 讨论影响胚胎移植成功的技术和程序因素.
主要成果:
- 人工智能和机器学习越来越多地用于优化试管婴儿刺激协议,评估生殖潜力和改善胚胎选择.
- 预测模型正在开发至关重要的结果,如胚胎细胞形成和euploidy.
- 胚胎移植仍然是一个依赖于技能的程序,导管类型和超声波指导等因素至关重要.
结论:
- 人工智能和机器学习正在通过实现数据驱动,个性化的治疗策略来改变试管婴儿.
- 尽管人工智能取得了进展,但人类因素,特别是在胚胎移植中,目前对于取得成功的试管婴儿结果至关重要.
- 未来的机器人整合可能会将人工智能的影响力扩展到目前以人为中心的程序,如胚胎移植.
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