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Table 2 MSE, RMSE, MAD, MAPE of each ANN model between the observed serum digoxin concentrations and the corresponding predicting concentrations on validation dataset

From: Predicting the serum digoxin concentrations of infants in the neonatal intensive care unit through an artificial neural network

ModelNo. of parametersParametersMAPE(%)MSERMSEMADR2(%)
111All Variables16.720.050.230.1963.00
210-Sex15.880.050.220.1765.17
39-Sex-DCM17.700.060.240.1974.46
48-Sex-DCM -PH15.030.040.200.1673.82
57-Sex-DCM -PH -Captopril21.410.090.300.2457.30
66-Sex-DCM -PH -Captopril -Furosemide23.180.090.290.2563.43
75-Sex-DCM -PH -Captopril -Furosemide -VSD25.160.110.330.2646.37
84-Sex-DCM -PH -Captopril -Furosemide -VSD -ibuprofen24.680.100.310.2644.43
  1. “- “in the column of parameters refers to “exclude” that specific variable from the model 1, which contain all variables. MAPE Mean Absolute Percentage Error; MSE Mean Square Error; RMSE Root Mean Square Error; MAD Mean Absolute Deviation, R2% determination of coefficient
  2. All 11 variables include: dose per total body weight, gender, postmenstrual age (PMA), Congestive heart failure (CHF), dilated cardiomyopathy (DCM), pulmonary hypertension (PH), Ventricular septal defect (VSD), with captopril, with furosemide, with ibuprofen
  3. *Common variables used in population pharmacokinetics were dose per total body weight, PMA, CHF