MACHINE LEARNING MODELS SU TO PREDICT KIDNEY STONE COMPOSITION AND 24-HOUR URINE ABNORMALITIES FROM ELECTRONIC HEALTH RECORD-DERIVED FEATURES

被引：0
|
作者：
Le, Chi
Kavoussi, Nicholas
Sui, Wilson
Bejan, Cosmin
Miller, Nicole
His, Ryan
机构：
来源：
JOURNAL OF UROLOGY | 2020年 / 203卷
关键词：
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：
PD35-03
引用
收藏
页码：E718 / E718
页数：1
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