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相关概念视频

Ovarian Cycle01:27

Ovarian Cycle

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The menstrual cycle includes a critical component known as the ovarian cycle, which undergoes two main phases each month—the follicular phase and the luteal phase. The follicular phase is variable and averaging around 14 days. Ovulation, triggered by a surge in luteinizing hormone (LH), marks the transition between the two phases. The second phase, the luteal phase, is relatively consistent, lasting approximately 14 days, and is marked by the activity of the corpus luteum. While a cycle...
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Hormonal Control of the Ovarian Cycle01:30

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The ovarian cycle is meticulously regulated by the hypothalamic-pituitary-gonadal axis. This cycle orchestrates the release of a mature oocyte, essential for reproduction.
Before puberty, the hypothalamus releases GnRH in a low frequency, low amplitude pulsatile manner. This along with the immature hypothalamic-pituitary-gonadal axis activity, results in low estrogen levels and the absence of a fully functional ovarian cycle.  At puberty, GnRH secretion increases in both frequency and...
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Reliability and Validity01:29

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Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
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In Vitro Drug Release Testing: Overview, Development and Validation01:10

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In vitro dissolution and drug release tests assess how quickly and how much of a drug is released from its dosage form into an aqueous medium under standardized laboratory conditions. These tests are essential tools in pharmaceutical development and quality assurance, offering insight into the drug's performance before clinical use.During formulation development, dissolution testing identifies incomplete or inconsistent drug release issues. It also supports decisions on selecting the optimal...
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Predicting Molecular Geometry02:27

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VSEPR Theory for Determination of Electron Pair Geometries
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Human behavior is intricately shaped by social influences that arise from interactions with others in diverse contexts. These influences not only mold beliefs and attitudes but also drive the regulation of behaviors through both direct communication and observational learning. The study of these processes falls within the domain of social psychology, which seeks to understand how individuals are affected by and affect those around them.Mechanisms of Social InfluenceDirect social influence...
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相关实验视频

Updated: Feb 5, 2026

Characterization and Functional Prediction of Bacteria in Ovarian Tissues
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个性化卵巢刺激和卵巢过度刺激综合征预防的综合预测系统:算法开发和验证.

Jingjing Chen1,2, Jianjuan Zhao3,4,5, Huiyu Qiu1,2

  • 1Department of Reproductive Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China.

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概括
此摘要是机器生成的。

这项研究开发了机器学习模型,以预测在生育治疗期间检索的卵细胞数量和卵巢过度刺激综合征风险. 该工具有助于优化卵泡刺激激素 (FSH) 剂量,以实现个性化的卵巢刺激.

关键词:
卵泡刺激激素 (FSH) 是一种激素.个性化卵巢刺激 个性化卵巢刺激机器学习是机器学习.卵巢过度刺激综合征是什么卵巢反应的反应

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科学领域:

  • 生殖内分泌学和不孕症研究.
  • 人工智能在临床决策支持系统中的应用.
  • 生物统计学和医疗保健中的预测建模.

背景情况:

  • 准确预测卵巢反应和最佳的卵泡刺激激素 (FSH) 剂量对于有效的卵巢刺激至关重要.
  • 目前的方法缺乏一个全面的模型,可以同时预测卵细胞产量和卵巢过度刺激综合征 (OHSS) 风险.

研究的目的:

  • 建立一个综合预测模型,用于预测取出的卵细胞数量 (NOR) 和评估早期发作的中度至严重的OHSS风险.
  • 在个性化卵巢刺激方案中指导FSH的最佳起始剂量.

主要方法:

  • 预后研究涉及患者进行他们的第一个卵巢刺激周期.
  • 使用大型内部和外部数据集开发和验证机器学习模型 (NOR为11,OHSS为11).
  • 在变量解释和基于网络的预测工具 (InOvaSGuide) 的开发中应用沙普利的增量解释.

主要成果:

  • 梯度增强回归器实现了NOR预测的高性能 (R2 ≈ 0.79).
  • 轻GBM模型显示OHSS预测的性能优越 (AUC ≈ 0.73-0.76).
  • 确定的关键预测因素包括FSH起始剂量与NOR的BMI比率以及OHSS的基线 antral毛囊数量.

结论:

  • 已经开发了一个综合框架,用于预测不同FSH剂量的NOR和OHSS风险.
  • 预测模型在一个用户友好的在线工具InOvaSGuide中实现.
  • 在临床实施之前,建议进一步进行前性评估.