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上海枫泾古镇一角_20240824上海枫泾古镇一角_20240824
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精准预测流产风险,上海交大等开发可解释AI算法,为早期预防带来希望

引言

流产,尤其是反复自然流产(RSM),是困扰许多女性的难题,不仅带来身体伤害,更在心理上造成深深的创伤。目前,临床监测手段大多为事后诊断,无法提前预防流产。上海交通大学李金金教授团队联合上海市红房子妇产科医院金莉萍副院长等,开发了基于人工智能的流产风险预警平台,首次实现了在怀孕前,通过分析血清代谢物来精准预测流产风险,为早期预防带来了希望。

技术创新:人工智能加持的流产风险预测

该团队利用可解释的人工智能算法,对临床数据和代谢组学数据进行深度挖掘和分析。通过对481名女性的血清样本进行分析,结合其他临床指标,构建了一种高精度的流产风险预测模型。这项技术首次将预孕期血清代谢物与流产风险联系在一起,并发现了组氨酸(Histidine)在流产风险预测中的关键作用。

揭秘组氨酸:从代谢物到流产风险预测的桥梁

研究团队发现,预孕期女性血清中组氨酸水平的异常升高与流产风险密切相关。组氨酸在体内会被转化为组胺(Histamine),而组胺的异常水平可能会在孕早期引发一系列不良反应,导致妊娠失败。

为了验证这一假设,研究团队使用小鼠模型进行实验,结果显示高组氨酸饮食会导致小鼠体内组氨酸水平显著升高,并最终引发了胚胎的吸收和丧失。这一实验结果与临床样本分析相呼应,证实了组氨酸-组胺代谢通路在流产风险预测中的重要性。

AI流产预测平台的临床应用与前景展望

AI流产预测平台的开发,为流产风险的早期预防开辟了新路径。该平台通过预孕期血清检测,结合AI算法的强大计算能力,为临床医生提供了一种精准的预警工具。

未来展望

这项研究为流产的早期预测和预防提供了科学依据,也为医学界带来了新的希望与方向。未来,研究团队将进一步探索组氨酸-组胺代谢通路与流产之间的关系,并开发更精准、更有效的流产预防策略,为更多女性带来福音。

参考文献

  1. Interpretable learning predicts miscarriage using pre-pregnancy serum metabolites. The Innovation Medicine, 2024. https://www.the-innovation.org/article/doi/10.59717/j.xinn-med.2024.100093


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