An evaluation of machine learning methods to improve the feasibility of fidelity monitoring of family-based prevention in primary care

被引：0
|
作者：
Berkel, Cady [1 ]
Knox, Dillon [2 ]
Flemotomos, Nikolaos [2 ]
Atkins, David [3 ]
Narayanan, Shri [2 ]
机构：
[1] Arizona State Univ, Phoenix, AZ USA
[2] Univ Southern Calif, Los Angeles, CA 90007 USA
[3] Univ Washington, Seattle, WA 98195 USA
来源：
IMPLEMENTATION SCIENCE | 2022年 / 17卷 / SUPPL 1期
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D O I：
暂无
中图分类号：
R19 [保健组织与事业（卫生事业管理）];
学科分类号：
摘要：
S90
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收藏
页数：2
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