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Table 3 The training data and the test data of the adjusted ultrasound results and the model fitting parameters

From: Comparing human milk macronutrients measured using analyzers based on mid-infrared spectroscopy and ultrasound and the application of machine learning in data fitting

  Data set (n = 465) Adjusted ultrasound 95% LOAa Mean squared error (MSE) Variance score Lin’s Concordance Correlation Coefficient P-valueb Model MSE Model Bias Model Variance
Fat (g/dl) Training data (n= 372) 3.14 ± 0.49 -0.91 ~ 0.91 0.217 0.551 0.67 0.13 0.233 0.231 0.002
Test data (n= 93) 3.23 ± 0.57 -0.93 ~ 0.97 0.231 0.670 0.67
Energy (kj/dl) Training data (n= 372) 270.26 ± 20.71 -41.42 ~ 41.42 445.401 0.499 0.71 0.60 333.67 330.35 3.321
Test data (n= 93) 271.52 ± 19.20 -34.92 ~ 36.58 329.751 0.465 0.78
  1. a refers to the result of Bland-Altman analysis between adjusted ultrasonic and MIR values; b refers to the p-value of t-test between training data and test data