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开发基于人工智能的支持系统,用于控制卵巢刺激

Yoshimasa Asada^1,2, Tomoya Shinohara³, Sho Yonezawa³

¹Asada Ladies Clinic Nagoya Japan.

Reproductive medicine and biology

|September 3, 2024

概括

开发了一个AI系统,以优化控制卵巢刺激 (COS) 协议用于体外受精 (IVF). 人工智能模型在预测卵细胞提取时间和药物处方方面表现出高准确性,有助于临床决策.

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:

控制性卵巢刺激 (COS) 是体外受精 (IVF) 程序的关键组成部分.
优化COS协议对于改善试管婴儿成功率和患者结果至关重要.
当前的COS协议通常依赖于医生的专业知识,这可能导致变化.

研究的目的:

开发和验证人工智能 (AI) 系统,以支持COS协议的实施.
创建人工智能模型来预测最佳卵细胞检索时间和推断药物处方.
提高COS在临床实践中的效率和一致性.

主要方法:

开发两个人工智能模型:一个卵细胞检索决策模型和一个处方推断模型.
培训人工智能模型,使用来自临床管理系统的试管婴儿治疗记录的全面数据集.
使用诸如曲线下的面积 (AUC),灵敏度和特异性等指标评估模型性能.

主要成果:

卵细胞检索决策模型实现了高AUC的0.964.
处方推断模型表现出强的性能,AUC为0.948.
系统中的个体预测模型 (hCG,hMG,Cetrorelix,Estradiol) 显示AUC值在0.914到0.976.6之间.

结论:

开发的AI系统在支持COS协议方面表现出高精度和临床实用性.
人工智能算法已在临床环境中成功地作为COS工具实施.
这种人工智能驱动的方法有可能在试管婴儿治疗中标准化和改进COS实践.

关键词:

人工智能的人工智能是人工智能.在体外受精体外受精.卵细胞检索卵细胞检索排卵诱导诱导排卵诱导医疗处方处方处方处方

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