【AKI】利用機器學習預測急性冠狀動脈綜合症患者顯影劑相關的急性腎損傷風險

 【AKI】利用機器學習預測急性冠狀動脈綜合症患者顯影劑相關的急性腎損傷風險

 文章出處  

Frontiers in Digital Health 

 

 原文標題  

An Interpretable XGBoost Model for Contrast-Associated Acute Kidney Injury in Patients With Acute Coronary Syndrome: Development and Geographical External Validatio 

 

 文章序號  

12405 

 

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