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Developing Federated Learning Strategies for Disease Surveillance Using Cross-Jurisdiction Electronic Medical Records without Data Sharing: With Applications to Sepsis Detection

Developing Federated Learning Strategies for Disease Surveillance Using Cross-Jurisdiction Electronic Medical Records without Data Sharing: With Applications to Sepsis Detection
在没有数据共享的情况下使用跨辖区电子病历开发疾病监测联合学习策略：应用于脓毒症检测
批准号：
464488
负责人：
Li Na
金额：
$0.0万
依托单位：
University of Calgary
依托单位国家：
加拿大
项目类别：
Operating Grants
财政年份：
2022
资助国家：
加拿大
项目状态：
已结题
起止时间：
2022-03-01 至 2023-03-01
来源：
https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=464488&lang=en
关键词：
Cross-Jurisdiction Research Detection Of Sepsis Diagnostic And Prognostic Prediction Disease Surveillance Electronic Medical Records Federated Learning Machine Learning Population Health Statistical Learning System Performance

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中文摘要
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英文摘要
Electronic Medical Records are secure, private, lifetime records containing patient-health and point-of-care histories within the healthcare system, which can be used for disease surveillance, clinical studies, and many others. It is hard to share and use
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