Pattern discrimination software for neonatal cardiovascular risk estimation

R. Hermida, J. R. Fernández, D. Ayala, F. Aguado
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Abstract

Parametric characteristics obtained by least-squares fitting and descriptive statistics of within-a-day variability in blood pressure and heart rate for 150 neonates are here used for classification according to a cardiovascular risk score by the use of an all-subsets variable selection technique for discriminant analysis, specifically designed for biomedical applications. Results provide a set of classification criteria for further use in neonatal risk assessment.1
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模式识别软件用于新生儿心血管风险评估
通过最小二乘拟合获得的参数特征和对150名新生儿血压和心率在一天内变异性的描述性统计,本文使用全子集变量选择技术进行判别分析,根据心血管风险评分进行分类,专为生物医学应用而设计。结果提供了一套分类标准,以进一步用于新生儿风险评估
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