ISRCTN10900816进行中(未招募)未知
An AI-driven fetal monitoring model to predict fetal growth restriction infants
niversity of Malaya0 个研究点目标入组 300 人开始时间: 2023年3月15日最近更新:
适应症
试验速览
- 阶段
- 未知
- 状态
- 进行中(未招募)
- 发起方
- 入组人数
- 300
研究概览
简要总结
暂无简介。
研究设计
- 研究类型
- Observational
入排标准
- 性别
- Female
入选标准
- •Inclusion criteria for Phases 1, 2 and 3:
- •1. Pregnant women with age of between 21 and 50 years
- •2. Subjects are already scheduled for routine antenatal ultrasound evaluation
排除标准
- •Phases 1 and 2:
- •1. Fetuses with chromosomal and cardiovascular abnormalities and cases with incomplete data
- •1. Patients who, for any reason, are deemed unfit for blood taking, as determined by their physician
- •2. Fetus with chromosomal and cardiovascular abnormalities
研究者
相似试验
招募中
不适用
Study of next-generation fetal monitoring diagnostic technology using fetal biosignalsPregnant women and their fetuses whose satisfy following conditions. 1)Age: More than 20 years old (the time of informed consent ) 2)Pregnant women over 34 weeks pregnant.JPRN-UMIN000037854Tohoku University125
尚未招募
Unknown
Comprehensive prediction model for Gestational Diabetrs Mellitus.CTRI/2023/08/056364Dr Tanya Khajuria
已完成
不适用
A study on the monitoring of the fetal state during anesthesia.Pregnant womanJPRN-UMIN000017414Tohoku University Hospital30
已完成
不适用
Development of an AI-based system for predicting falls and fall-related injuries in hospitalsone (All patients admitted during the study period)JPRN-UMIN000041289Fujita Health University69,291
已完成
Unknown
A study of a Predictive Data Model for maternal mental health depression using a Commercial Wearable DeviceHealthy pregnant woman or nursing motherJPRN-UMIN000051454Hakodate Central General hospital40
