在整个体外受精周期中应用人工智能的当前进展和现有挑战.
Yuanxu Gao1,2, Yifeng Yuan3,4,5,6, Kai Wang1
1Department of Big Data and Biomedical AI, College of Future Technology, Peking University and Peking-Tsinghua Center for Life Sciences, Beijing 100871, China.
Patterns (New York, N.Y.)
|December 2, 2025
概括
通过分析各种数据,人工智能 (AI) 可以增强体外受精 (IVF) 治疗的决策. 人工智能普遍性,偏见和对公平实施的验证仍然存在挑战.
科学领域:
- 生殖医学 生殖医学
- 人工智能的人工智能
- 生物医学数据科学 生物医学数据科学
背景情况:
- 体外受精 (IVF) 的成功率受到复杂性和临床经验的限制.
- 人工智能 (AI) 提供了改善试管婴儿决策的机会.
- 需要对人工智能在试管婴儿中的应用进行全面审查.
研究的目的:
- 审查目前在试管婴儿中的人工智能应用,按数据模式分类.
- 评估人工智能模型的性能和方法上的进步.
- 探索新兴的人工智能方法并确定实施挑战.
主要方法:
- 对在试管婴儿中应用人工智能的研究进行系统审查.
- 基于数据类型的AI应用程序的分类:结构化健康记录,生物医学图像和omics数据.
- 对人工智能模型性能,任务表示和方法进度的分析.
主要成果:
- 人工智能应用在IVF中的结构化数据,成像和omics中是多样化的.
- 新兴的人工智能方法,如多模式学习和大型语言模型,显示出潜力.
- 关键的挑战包括有限的概括性,数据偏差和临床验证的需要.
结论:
- 在试管婴儿中整合人工智能对改善治疗有很大的前景.
- 严格的验证,道德考虑和透明度对于成功实施AI至关重要.
- 跨学科的合作对于在IVF中安全和公平地采用AI至关重要.
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