Association rule analysis for fetal heart rate pattern of late FGR

胎心率 心电图 斯皮尔曼秩相关系数 相关性 主成分分析 胎儿 内科学 医学 计算机科学 人工智能 机器学习 心率 怀孕 数学 生物 血压 几何学 遗传学
作者
Liyan Zhong,Shiyao Huang,Xia Li,Guiqing Liu,Qinqun Chen,Xiaomu Luo,Yuexing Hao,Jiaming Hong,Hang Wei
标识
DOI:10.1109/bibm55620.2022.9995462
摘要

Late fetal growth restriction (FGR) is a common complication of pregnancy characterized by chronic hypoxia. However, late FGR is in a dilemma of the high incidence but low detection rate. Depending on the non-invasiveness and convenient operation, the routine cardiotocography (CTG) allows continuous monitoring fetal heart rate (FHR) to assess fetal intrauterine stockpiling ability. In this paper, we aimed to explore the FHR pattern of late FGR in routine CTG. For analysis, the FHR features were acquired using routine CTG in a population of 160 healthy and 102 late FGR fetuses published in IEEE Dataport. First, we explored the relationships among FHR features and their importance on late FGR assessment by utilizing hypothesis testing, principal component analysis (PCA) and Spearman correlation analysis. Second, we presented a regression coefficient-based backward-stepwise-selection of association rules analysis (ARA) called backward-stepwise Max-R 2 Apriori ARA, to find the optimum itemset that helps diagnose late FGRs from healthy fetuses. The hypothesis testing, PCA and Spearman correlation analysis found eight FHR features were highly relevant to the late FGR. Moreover, the backward-stepwise Max-R2 Apriori ARA validated the correlation and interpretation about FHR features of late FGR. In conclusion, the analysis results are consistent with clinical knowledge on late FGR and help screen late FGR in antepartum fetal monitoring.
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