[摘要]多囊卵巢综合征是临床常见的内分泌系统疾病，其发病机制至今尚未明确，但已知与遗传、环境等因素相关。本文根据预防为主、防治结合的诊疗思路，采用联邦学习技术融合多种算法构建平台，通过信息数据采集及管理、预测模型建立、实施风险评估和健康指导3个基本环节，在保证女性医疗隐私数据安全的前提下，以期实现对女性健康状态的连续追踪、反馈和疾病的精准预防、高效治疗。

    [关键词]多囊卵巢综合征；联邦学习；预测

    [中图分类号]R711.75[文献标志码]A[文章编号]2096-5532(2023)03-0458-04

    doi：10.11712/jms.2096-5532.2023.59.083[开放科学(资源服务)标识码(OSID)]

    [网络出版]https：//kns.cnki.net/kcms2/detail/37.1517.R.20230726.1033.001.html;2023-07-2616：29：45

    CONSTRUCTION OF A PREDICTION PLATFORM FOR POLYCYSTIC OVARY SYNDROME BASED ON FEDERATED LEARNING" SUN Ye， REN Jian， TIAN Qi， YUAN Mengqi， XU Yan (College of Traditional Chinese Medicine， Shandong University of Chinese Medicine，Jinan" 250355， China)

    [ABSTRACT]Polycystic ovary syndrome is a common endocrine system disease in clinic. Its pathogenesis has not been clarified yet， but it is known to be related to genetic and environmental factors. Based on the diagnosis and treatment idea of prevention first and prevention and treatment combination ......