Prediction of Multiple Organ Failure Complicated by Moderately Severe or Severe Acute Pancreatitis Based on Machine Learning: A Multicenter Cohort Study
Table 3
Comparison of the predictive performance of different models in optimal feature subset in test set.
Variable
LR (95%CI)
QDA (95%CI)
NB (95%CI)
SVM (95%CI)
Adaboost (95%CI)
BP (95%CI)
value
SEN
58.54% (42.20%-73.30%)
60.98% (44.54%-75.38%)
73.17% (56.69%-85.25%)
60.98% (44.54%-75.38%)
80.49% (64.63%-90.63%)
75.61% (59.36%-87.09%)
0.15
SPE
93.33% (84.47%-95.52%)a,c,d,e
86.67% (76.39%-93.08%)d
76.00% (64.50%-84.79%)b
89.33% (79.54%-94.95%)d
73.33% (61.66%-82.58%)a,b,f
74.67% (63.08%-83.69%)a,b
0.001
FPR
6.67% (1.02%-12.32%)a,c,d,e
13.33% (5.64%-21.03%) d
24.00% (14.33%-33.67%) b
10.67% (3.68%-17.66%) d
26.67% (16.66%-36.67%) a,b,f
25.33% (15.49%-35.17%) a,b
0.001
FNR
41.46% (26.38%-56.54%)
39.02% (24.09%-77.80%)
26.83% (13.27%-40.39%)
39.02% (24.09%-77.80%)
19.51% (7.38%-31.64%)
24.39% (11.25%-37.53%)
0.15
PPV
82.76% (63.51%-93.47%)
71.43% (53.48%-84.76%)
62.50% (47.33%-75.68%)
75.76% (57.37%-88.26%)
62.26% (47.87%-74.88%)
62.00% (47.16%-75.00%)
0.281
NPV
93.33% (84.47%-97.52%)
80.25% (69.61%-87.95%)
83.82% (72.47%-91.27%)
80.72% (70.29%-88.25%)
87.30% (75.96%-93.97%)
84.85% (73.44%-92.11%)
0.87
Accuracy
80.3% (73.0-87.7%)
78.5% (71.1-85.9%)
75.0% (67.0-83.0%)
79.3% (71.8-86.8%)
75.9% (68.0-83.8%)
75.0% (67.0-83.0%)
0.831
AUC
0.782 (0.694-0.853)
0.785 (0.686-0.848)
0.779 (0.688-0.849)
0.772 (0.679-0.842)
0.826 (0.740-0.888)
0.805 (0.714-0.869)
/
aCompared with QDA, ;bCompared with LR, ;cCompared with NB, ;dCompared with AdaBoost, ;eCompared with BP, ;fCompared with SVM, . value denoted the overall statistical result for the four models.
