Computational Approaches for Connecting Maternal Stress to Preterm Birth

被引：0
|
作者：
Mirzaei, Amin [1 ]
Hiller, Bjarne C. [1 ]
Stelzer, Ina A. [2 ]
Thiele, Kristin [4 ]
Tan, Yuqi [3 ]
Becker, Martin [1 ]
机构：
[1] Univ Rostock, Inst Informat, Dept Comp Sci & Elect Engn, Albert Einstein Str 22, D-18059 Rostock, Germany
[2] Univ Calif San Diego, Dept Pathol, GPL CMM-West 9500 Gilman Dr, La Jolla, CA 92093 USA
[3] Stanford Univ, Sch Med, Dept Microbiol & Immunol, CSSR3220,269 Campus Dr, Stanford, CA 94305 USA
[4] Univ Med Ctr Hamburg Eppendorf, Dept Obstet & Fetal Med, Div Expt Feto Maternal Med, Martinistr 52, D-20246 Hamburg, Germany
来源：
CLINICS IN PERINATOLOGY | 2024年 / 51卷 / 02期
基金：
美国国家卫生研究院;
关键词：
Stress; Preterm birth; Machine learning; Artificial intelligence; PREGNANCY; DISTRESS; DELIVERY; RISK;
D O I：
10.1016/j.clp.2024.02.003
中图分类号：
R71 [妇产科学];
学科分类号：
100211 ;
摘要：
[No abstract available]
引用
收藏
页码：345 / 360
页数：16
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