在受控的卵巢过度刺激中使用淋巴激素起始剂量的预测模型:审查和进展更新
Xiaoxiao Guo1, Hao Zhan2, Xianghui Zhang1
1Department of Reproductive Medicine, Binzhou Medical University Hospital, Binzhou City, Shandong Province, China.
Human fertility (Cambridge, England)
|December 1, 2023
概括
确定开始性腺激素 (Gn) 剂量对于受控的卵巢高刺激 (COH) 在试管婴儿中至关重要. 研究正在探索人工智能和深度学习,以创建更准确的预测模型,以获得最佳的 Gn 剂量.
科学领域:
- 生殖医学 生殖医学
- 生物技术是生物技术.
- 医疗保健中的人工智能
背景情况:
- 控制的卵巢过度刺激 (COH) 是体外受精-胚胎移植 (IVF-ET) 的基础.
- 淋巴激素 (Gn) 的起始剂量显著影响卵细胞产量,周期取消和怀孕结果.
- 尽量减少卵巢过度刺激综合征 (OHSS) 等并发症是ART的一个关键目标.
研究的目的:
- 突出标准化和准确的Gn初始剂量确定在COH中至关重要的重要性.
- 审查过去二十年来 Gn 起始剂量预测模型的演变.
- 探索人工智能 (AI) 和深度学习在开发未来预测模型方面的潜力.
主要方法:
- 对 Gn 起始剂量预测模型现有研究的综述.
- 在COH中影响Gn剂量选择的因素分析.
- 探索用于预测建模的AI和深度学习方法.
主要成果:
- 个性化的Gn起始剂量对于成功的IVF-ET结果至关重要.
- 之前的研究重点是开发 Gn 剂量的各种预测模型.
- 人工智能和深度学习有望提高这些模型的准确性.
结论:
- 精确的Gn起始剂量选择对于优化辅助生殖技术 (ART) 中的COH协议至关重要.
- 人工智能和深度学习的整合预计将导致更精确,更有效的GN剂量预测模型.
- 未来的研究应该专注于开发和验证人工智能驱动的工具,以实现个性化的 Gn 剂量管理.
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