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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