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• W2034631231 abstract "ABSTRACT A statistical process control (SPC)-based methodology is developed to detect early deviations of fetal biometry from expected normal growth. Using response modeling methodology (RMM), a fetal growth model is dynamically estimated and integrated in a regression-adjusted SPC control scheme, based on a new median control chart and a control chart for residuals variation. Hadlock's reference centiles are also integrated in the monitoring scheme. Longitudinal data from normal pregnancies and those with adverse medical outcomes have been analyzed. Results show that nonsmooth growth trajectory, expressed in exceptionally large absolute deviations from predicted median values, is a good precursor to possible prenatal adverse outcomes. KEYWORDS: customized fetal growth modeling and monitoringleast absolute deviationnonlinear profilesresponse modeling methodologyshort runsstatistical process control Notes a m =number of observations for model estimation; Bio. = biometric measure (mm). b LAD*is based on sum of absolute deviations (of m observations used for model fitting). a Estimates of parameters of fitted Laplace distribution (LAD*, normal pregnancies): {μ p , β p , Q 0.97725}: AC-HC: {4.28, 2.48, 11.9}; BPD-FL = {1.22, 0.682, 3.51}. Q p = 100p% percentile. a j*is an ordinal index of selected data point constrained to have zero residual. For location parameter L, minimal biometric value in the sample is displayed in brackets. Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/lqen." @default.
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• W2034631231 date "2014-05-27" @default.
• W2034631231 modified "2023-10-04" @default.
• W2034631231 title "Customized Fetal Growth Modeling and Monitoring—A Statistical Process Control Approach" @default.
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• W2034631231 doi "https://doi.org/10.1080/08982112.2013.830742" @default.
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