| 移动边缘计算环境下基于联邦机器学习的医联体慢病管理 |
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| 引用本文： | 姚俊明,邢丹,邵婷婷. 移动边缘计算环境下基于联邦机器学习的医联体慢病管理[J]. 医学信息学杂志, 2020, 41(11): 17-21 |
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| 作者姓名： | 姚俊明 邢丹 邵婷婷 |
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| 作者单位： | 济宁医学院医学信息工程学院 日照 276826 |
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| 基金项目： | 济宁医学院教师科研扶持基金“移动云环境下医疗健康服务研究”（项目编号：JYFC2018 KJ064）；济宁医学院医学人文素质专项“基于移动群智感知的医学生人文素质教育评价研究”（项目编号：NO：34）。 |
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| 摘 要： | 介绍健康医疗数据应用发展情况及相关研究现状，提出采用联邦机器学习方式建立具有安全和隐私保护的慢病管理模型，从目的、系统架构、框架及功能、训练过程等方面阐述模型框架设计，指出其有助于大幅降低用户数据泄露风险。
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| 关 键 词： | 移动边缘计算 联邦机器学习 医疗联合体 |
| 收稿时间： | 2020-04-03 |
Chronic Disease Management of Medical Alliance Based on Federated Machine Learning under the Mobile Edge Computing Environment |
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| YAO Junming,XING Dan,SHAO Tingting. Chronic Disease Management of Medical Alliance Based on Federated Machine Learning under the Mobile Edge Computing Environment[J]. Journal of Medical Informatics, 2020, 41(11): 17-21 |
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| Authors: | YAO Junming XING Dan SHAO Tingting |
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| Affiliation: | School of Medical Information Engineering of Jining Medical University, Rizhao 276826, China |
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| Abstract: | The paper introduces the application and development situation of health care data and related study status, proposes to establish a chronic disease management model with safety and privacy protection by using federated machine learning method, expounds the model framework design from the aspects of objectives, system architecture, framework and functions, training process, etc., points out that it is helpful to greatly reduce the risk of user data leakage. |
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| Keywords: | mobile edge computing federated machine learning medical alliance |
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