基于人工智能的最佳治疗策略选择女性不孕症的第一个和随后的IVF-ET周期
Renjie Wang1, Wei Pan2, Lean Yu3
1Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, PR China.
Journal of medical systems
|August 16, 2023
概括
中国中国中国中国.
科学领域:
- 生殖医学 生殖医学
- 医疗保健中的人工智能
- 临床决策支持系统 临床决策支持系统
背景情况:
- 中国不孕率上升 (12.5%-15%) 需要改进治疗策略.
- 试管受精和胚胎移植 (IVF-ET) 是至关重要的,但面临着成功率 (30%-40%) 和成本上升的挑战.
- 目前的IVF-ET治疗选择依赖于医生的经验,缺乏标准化的协议.
研究的目的:
- 开发基于人工智能 (AI) 的系统,以选择最佳的IVF-ET治疗策略.
- 通过数据驱动的决策来提高IVF-ET成功率并降低治疗成本.
- 根据患者个体特征提供个性化的治疗建议.
主要方法:
- 开发了一个人工智能系统来分析临床数据并模仿IVF-ET过程.
- 评估了十种不同的AI分类算法,以预测患者怀孕结果.
- 实施特征排名,以确定患者特征在治疗成功中的重要性.
主要成果:
- 在10个AI分类算法中,性能各不相同,这凸显了最佳方法选择的必要性.
- 功能排名确定了影响IVF-ET结果的关键患者特征.
- 人工智能系统展示了提高诊断准确性和治疗效率的潜力.
结论:
- 基于人工智能的方法可以有效地从临床数据中提取IVF-ET治疗选择的隐性知识.
- 选择最佳的人工智能算法对于在IVF-ET中准确预测怀孕至关重要.
- 基于患者特征的个性化治疗建议可以提高IVF-ET的结果和效率.
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