Utilizing machine learning to determine the most appropriate method to predict 90-day home-time after stroke and the contribution of clinically relevant covariates to differences in 90-day home-time among men and women
Utilizing machine learning to determine the most appropriate method to predict 90-day home-time after stroke and the contribution of clinically relevant covariates to differences in 90-day home-time among men and women
利用机器学习确定预测中风后 90 天在家时间的最合适方法，以及临床相关协变量对男性和女性 90 天在家时间差异的贡献
批准号：
397125
负责人：
Holodinsky Jessalyn K
金额：
$6.56万
依托单位国家：
加拿大
项目类别：
Fellowship Programs
财政年份：
2018
资助国家：
加拿大
项目状态：
已结题
起止时间：
2018-11-01 至 2020-11-01
中文摘要
翻译
中风是加拿大致残和死亡的主要原因之一。然而，中风对男性和女性的影响不同。与男性相比，女性在中风后会经历更大的残疾。造成这些差异的原因尚不清楚，也很难弄清
英文摘要
Stroke is one of the leading causes of disability and death in Canada. However, stroke affects men and women differently. Women experience greater disability compared to men after stroke. The reasons for these differences are unknown and are difficult to
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科研奖励(0)
会议论文
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批准号：440368
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项目类别：Fellowship Programs
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资助金额：$3.28万
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财政年份：2020
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依托单位：
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批准号：382907
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项目类别：
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资助金额：$0.07万
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财政年份：2018
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负责人：Holodinsky Jessalyn K
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依托单位：
Drip 'n Ship versus Direct to Thrombectomy Centre: Conditional Probability Modelling in Ireland
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批准号：364301
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项目类别：
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资助金额：$0.07万
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财政年份：2017
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负责人：Holodinsky Jessalyn K
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依托单位：
海外基金
