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Table 3 Prediction ability of the nephrologists compared to ANNs

From: Would artificial neural networks implemented in clinical wards help nephrologists in predicting epoetin responsiveness?

  Nephrologists ANN
Mean absolute error 0.24 -0.02
SD 0.8972 0.8184
CRMSE 0.9279 0.8186
LA -1.5577 -1.6519
  2.0311 1.6218
95%CI bias 0.1310 -0.1115
  0.3424 0.0814
95% CI lower -1.7408 -1.8189
  -1.3746 -1.4849
95% CI upper 1.8480 1.4548
  2.2142 1.7889
NMSE 0.8020 0.6239
r Pearson 0.5337 0.6135
r /NMSE 0.6654 0.9831
  1. Accuracy expressed by the Combined Root Mean Square Error (CRMSE) and agreement expressed by the "limits of agreement" (LA), the "95% confidence interval for the bias" (95% CI bias), the "95% confidence interval for the lower (95% CI lower) and upper (95% CI upper) limits of agreement", the Normalized Mean Squared Error (NMSE), the Pearson linear correlation r and the r/NMSE ratio in the prediction of the haemoglobin one month later.