MACHINE LEARNING MODELS TO PREDICT 24-HOUR URINE ABNORMALITIES FROM ELECTRONIC HEALTH RECORD-DERIVED FEATURES

被引：0
|
作者：
Kavoussi, Nicholas
Abraham, Abin
Sui, Wilson
Bejan, Cosmin
Capra, John
Hsi, Ryan
机构：
来源：
JOURNAL OF UROLOGY | 2021年 / 206卷
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D O I：
暂无
中图分类号：
R5 [内科学]; R69 [泌尿科学（泌尿生殖系疾病）];
学科分类号：
1002 ; 100201 ;
摘要：
MP54-19
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页码：E957 / E957
页数：1
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