Prediction of Multiple Organ Failure Complicated by Moderately Severe or Severe Acute Pancreatitis Based on Machine Learning: A Multicenter Cohort Study
Table 2
Comparison of the predictive performance of different models in optimal feature subset in validation set.
Variable
LR (95% CI)
QDA (95% CI)
NB (95% CI)
SVM (95% CI)
AdaBoost (95% CI)
BP (95% CI)
value
SEN
65.4% (55.2-74.5%)a,c,d,e
83.2% (75.7-90.6%)b
81.2% (73.4-88.9%)b
71.3% (62.3-80.3%)
80.2% (72.3-88.1%)b
83.2% (75.7-90.6%)b
0.008
SPE
90.0% (85.4-93.6%)
77.4% (71.5-82.4%)
78.3% (72.4-83.2%)
83.9% (78.6-88.3%)
80.4% (75.3-85.6%)
76.5% (71.0-82.0%)
0.002
FPR
10.0% (6.4-14.9%)
22.6% (17.6-28.5%)
21.7% (16.8-27.6%)
16.1% (11.7-21.4%)
19.57% (14.4-24.7%)
23.5% (18.0-29.0%)
0.002
FNR
35.6% (25.5-46.8%)a,c,d,e
16.8% (9.4-24.3%)b
9.1% (11.1-26.6%)b
28.7% (10.7-37.7%)
19.8% (11.9-27.7%)b
26.8% (9.4-24.3%)b
0.008
PPV
73.3% (64.0-82.6%)
61.3% (53.1-69.6%)a
61.7% (53.3-70.0%)b,c
65.5% (56.4-74.5%)a
64.3% (55.8-72.8%)
60.9% (52.6-69.1%)
0.437
NPV
85.5% (81.0-90.0%)
91.2% (87.2-95.3%)
90.4% (86.3-94.5%)
86.9% (82.4-91.4%)
90.2% (86.1-94.3%)
91.2% (87.2-95.2%)
0.239
Accuracy
82.2% (78.0-86.3%)
78.9% (74.4-83.3%)
78.9% (74.4-83.3%)
79.8% (75.4-81.4%)
80.4% (76.1-84.7%)
78.5% (74.1-83.0%)
0.862
AUC
0.840 (0.796-0.878)
0.865 (0.824-0.900)
0.864 (0.823-0.899)
0.839 (0.795-0.877)
0.863 (0.821-0.898)
0.862 (0.820-0.897)
/
aCompared with QDA, ;bCompared with LR, ;cCompared with NB, ;dCompared with AdaBoost, ;eCompared with BP, . value denoted the overall statistical result for the four models.
