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Table 5 Survival prediction

From: Data analytics and clinical feature ranking of medical records of patients with sepsis

method

MCC

F1 score

accuracy

TP rate

TN rate

MLP

0.31±0.12

0.43±0.11

0.67±0.08

0.75±0.12

0.70±0.07

DL

0.16±0.10

0.30±0.07

0.72±0.05

0.50±0.12

0.82±0.07

NB

0.15±0.11

0.28±0.08

0.82±0.05

0.21±0.12

0.92±0.06

RF

0.15±0.10

0.28±0.08

0.64±0.05

0.58±0.16

0.65±0.06

LR

0.13±0.12

0.26±0.08

0.69±0.05

0.45±0.20

0.73±0.06

SVM (linear)

0.11±0.13

0.26±0.12

0.72±0.09

0.46±0.19

0.71±0.11

DT

0.10±0.12

0.25±0.11

0.69±0.08

0.39±0.17

0.74±0.09

SVM (kernel)

0.09±0.11

0.24±0.09

0.72±0.06

0.38±0.16

0.75±0.08

k-NN

0.08±0.13

0.22±0.09

0.69±0.11

0.38±0.24

0.73±0.15

method

PR AUC

ROC AUC

PPV

NPV

 

MLP

0.29±0.07

0.86±0.13

0.94±0.07

0.19±0.07

 

DL

0.20±0.06

0.86±0.18

0.88±0.05

0.19±0.13

 

NB

0.07±0.06

0.80±0.28

0.88±0.03

0.31±0.16

 

RF

0.32±0.06

0.86±0.25

0.91±0.04

0.19±0.07

 

LR

0.24±0.05

0.86±0.24

0.90±0.04

0.20±0.08

 

SVM (linear)

0.27±0.11

0.83±0.24

0.90±0.04

0.19±0.08

 

DT

0.23±0.08

0.90±0.23

0.89±0.04

0.19±0.09

 

SVM (kernel)

0.20±0.07

0.80±0.24

0.89±0.04

0.19±0.07

 

k-NN

0.23±0.13

0.91±0.21

0.89±0.05

0.18±0.11

 
  1. Performance of the learned models with the different methods evaluated with the different metrics, expressed in the format “average value ± standard deviation”, obtained on 100 executions. DT: decision tree. k-NN: k-nearest neighbors. DL: deep neural network with 3 hidden layers and weight decay. LR: logistic regression. NB: naive Bayes. MLP: multi-layer perceptron neural network. SVM (kernel): support vector machine with kernel. SVM (linear): linear support vector machine. MCC: Matthews correlation coefficient. TP rate: true positive rate (sensitivity, recall). TN rate: true negative rate (specificity). PR: precision-recall curve. ROC: receiver operating characteristic. AUC: area under the curve. MCC: worst value –1.00 and best value +1.00. PPV: positive predictive value (precision). NPV: negative predictive value. F1 score, accuracy, TP rate, TN rate, PR AUC, ROC AUC, PPV, NPV: worst value 0.00 and best value 1.00. Imbalance of this dataset: survived patients’ class: 1’s positives, #elements = 316 (86.81%), and deceased patients’ class: 0’s negatives, #elements = 48 (13.19%)