Table 2 The efficacy (precision, sensitivity and F1 score) of top three machine-learning classifiers in the training (A) and testing (B) sets (using imputed data).
From: Early predictive values of clinical assessments for ARDS mortality: a machine-learning approach
Datasets | Models | Predictive values for survivors (Day 0 = 498, Day 3 = 516) | Predictive values for non-survivors (Day 0 = 202, Day 3 = 158) | ||||
---|---|---|---|---|---|---|---|
Precision (95% CI) | Sensitivity (95% CI) | F1 score (95% CI) | Precision (95% CI) | Sensitivity (95% CI) | F1 score (95% CI) | ||
A. In the training set | |||||||
Day 0 (n = 700) | RF | 0.85 (0.83, 0.88) | 0.98 (0.98, 1.0) | 0.91 (0.91, 0.93) | 0.96 (0.93, 0.99) | 0.59 (0.54, 0.66) | 0.73 (0.69, 0.78) |
XGBoost | 0.87 (0.86, 0.9) | 0.98 (0.98, 0.99) | 0.92 (0.92, 0.94) | 0.95 (0.92, 0.98) | 0.66 (0.61, 0.72) | 0.78 (0.74, 0.82) | |
SVM | 0.94 (0.93, 0.97) | 0.98 (0.98, 1.0) | 0.96 (0.96, 0.98) | 0.97 (0.95, 0.99) | 0.87 (0.83, 0.91) | 0.91 (0.89, 0.94) | |
Day 3 (n = 674) | RF | 0.90 (0.88, 0.92) | 0.99 (0.98, 1.0) | 0.94 (0.93, 0.96) | 0.95 (0.92, 0.98) | 0.65 (0.6, 0.72) | 0.77 (0.73, 0.82) |
SVM | 0.89 (0.87, 0.92) | 0.97 (0.97, 0.99) | 0.93 (0.92, 0.95) | 0.89 (0.84, 0.94) | 0.62 (0.57, 0.69) | 0.73 (0.69, 0.78) | |
SC | 0.89 (0.87, 0.92) | 0.98 (0.98, 1.0) | 0.93 (0.93, 0.95) | 0.94 (0.9, 0.98) | 0.62 (0.56, 0.68) | (0.7, 0.8) |
Datasets | Models | Predictive values for survivors (n, Day 0 = 233, Day 3 = 215) | Predictive values for non-survivors (n, Day 0 = 67, Day 3 = 74) | ||||
---|---|---|---|---|---|---|---|
Precision (95% CI) | Sensitivity (95% CI) | F1 score (95% CI) | Precision (95% CI) | Sensitivity (95% CI) | F1 score (95% CI) | ||
B. In the testing set | |||||||
Day 0 (n = 300) | RF | 0.81 (0.78, 0.85) | 0.91 (0.88, 0.94) | 0.86 (0.83, 0.89) | 0.47 (0.34, 0.61) | 0.28 (0.19, 0.38) | 0.35 (0.25, 0.45) |
LR | 0.80 (0.77, 0.85) | 0.93 (0.9, 0.95) | 0.86 (0.84, 0.89) | 0.48 (0.34, 0.63) | 0.23 (0.16, 0.33) | 0.32 (0.22, 0.42) | |
MLP | 0.84 (0.81, 0.89) | 0.8 (0.76, 0.85) | 0.82 (0.79, 0.85) | 0.41 (0.33, 0.51) | 0.49 (0.39, 0.59) | 0.45 (0.36, 0.53) | |
Day 3 (n = 289) | RF | 0.82 (0.78, 0.86) | 0.95 (0.93, 0.98) | 0.88 (0.86, 0.91) | 0.76 (0.65, 0.88) | 0.39 (0.3, 0.49) | 0.51 (0.42, 0.61) |
XGBoost | 0.82 (0.78, 0.86) | 0.93 (0.91, 0.97) | 0.87 (0.85, 0.9) | 0.69 (0.58, 0.82) | 0.40 (0.31, 0.5) | 0.51 (0.42, 0.6) | |
SC | 0.82 (0.78, 0.86) | 0.95 (0.93, 0.98) | 0.88 (0.86, 0.91) | 0.76 (0.65, 0.88) | 0.40 (0.31, 0.5) | 0.53 (0.43, 0.62) |