基于预测风险评价的模糊聚类方法预测新生儿风险

Jyothi Thomas, G. Kulanthaivel
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引用次数: 0

摘要

宫颈在早产发病机制中的作用是有争议的。在一项前瞻性、多中心的孕妇研究中,我们使用阴道超声检查来测量子宫颈的长度;我们还记录了妊娠35周前自然分娩的发生率。我们对单胎妊娠妇女进行了大约24周和28周的阴道超声检查。然后我们评估子宫颈长度与自然早产风险之间的关系。我们对2915名怀孕约24周的妇女和其中2531名怀孕约28周的妇女进行了检查。在24周检查的126名妇女(4.3%)发生自发性早产(少于35周)。宫颈长度在24周和28周呈正态分布(平均[SD]分别为35.28.3 mm和33.78.5 mm)。早产的相对风险随着子宫颈长度的减小而增加。本文讨论了其他可能由人工神经网络实现的非线性的近似性质。每天的登记有N个案例,每个案例都是众所周知的刺激-答案对所代表的。这项工作的目标是开发一个函数,它允许找到入口变量向量t到出口变量向量p的向量F是任何函数,在这种情况下是电力消耗。它们的人工神经网络(ANN)建模是多感知器层(PMC)。另一种建模形式是使用插值算法(AI)。对于28周测量的长度,相应的相对风险为2.80,3.52,5.39,9.57,13.88和24.94 (P0.001值在或低于第50百分位;第75个百分位数的值为P0.003)。在怀孕期间阴道超声检查发现宫颈短的妇女自然早产的风险增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting the risk of newborns based on fuzzy clustering method with prediction risk assessment
The role of the cervix in the pathogenesis of premature delivery is controversial. In a prospective, multicenter study of pregnant women, we used vaginal ultrasonography to measure the length of the cervix; we also documented the incidence of spontaneous delivery before 35 weeks' gestation. We performed vaginal ultrasonography at approximately 24 and 28 weeks of gestation in women with singleton pregnancies. We then assessed the relation between the length of the cervix and the risk of spontaneous preterm delivery. We examined 2915 women at approximately 24 weeks of gestation and 2531 of these women again at approximately 28 weeks. Spontaneous preterm delivery (at less than 35 weeks) occurred in 126 of the women (4.3 percent) examined at 24 weeks. The length of the cervix was normally distributed at 24 and 28 weeks (mean [SD], 35.28.3 mm and 33.78.5 mm, respectively). The relative risk of preterm delivery increased as the length of the cervix decreased. The paper discusses approximation properties of other possible types of nonlinearities that might be implemented by artificial neural networks. The daily registration has N cases that each of the well-known stimulus-answer couples represents. The objective of this work is to develop a function that allows finding the vector of entrance variables t to the vector of exit variables P. F is any function, in this case the electric power consumption. Their modeling with Artificial Neural Network (ANN) is Multi a Perceptron Layer (PMC). Another form of modeling it is using Interpolation Algorithms (AI). For the lengths measured at 28 weeks, the corresponding relative risks were 2.80, 3.52, 5.39, 9.57, 13.88, and 24.94 (P0.001 for values at or below the 50th percentile; P0.003 for values at the 75th percentile). The risk of spontaneous preterm delivery is increased in women who are found to have a short cervix by vaginal ultrasonography during pregnancy.
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