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DynaMELD: Leveraging Deep Neural Networks and Time Varying Covariates to Equitably Assess Mortality Risk in Patients Waitlisted for Liver Transplant

DynaMELD: Leveraging Deep Neural Networks and Time Varying Covariates to Equitably Assess Mortality Risk in Patients Waitlisted for Liver Transplant
DynaMELD：利用深度神经网络和时变协变量公平评估肝移植候补患者的死亡风险
批准号：
465728
负责人：
Cooper Michael J
金额：
$2.55万
依托单位：
University Health Network (Toronto)
依托单位国家：
加拿大
项目类别：
Fellowship Programs
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=465728&lang=en
关键词：
End-Stage Liver Disease Liver Transplant Sex-Based Inequity Waitlist Mortality

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英文摘要
An accurate, equitable estimation of pre-transplant mortality is an essential component of fairly prioritizing patients for liver transplant. For the past 20 years, transplant centers in the United States and Canada have relied on the Model for End-Stage
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