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
批准号:
464488
负责人:
Li Na
金额:
$0.0万
依托单位:
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
中文摘要
电子医疗记录是一种安全、隐私的终身记录,其中包含医疗保健系统中的患者健康和护理点历史记录,可用于疾病监测、临床研究和许多其他方面。很难分享和使用
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
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Optimizing Resource Allocation through Data-Driven Patient Segmentation: A Machine Learning Approach to Enhance Outpatient and Home Transfusion Services
-
批准号:493337
-
项目类别:
-
资助金额:$0.15万
-
财政年份:2023
-
负责人:Li Na
-
依托单位:
Developing Federated Learning Strategies for Disease Surveillance Using Cross-Jurisdiction Electronic Medical Records without Data Sharing: With Applications to Acute Myocardial Infarction, Hypertension, and Sepsis Detection
-
批准号:468573
-
项目类别:Operating Grants
-
资助金额:$51.27万
-
财政年份:2022
-
负责人:Li Na
-
依托单位:
海外基金