Table 4 Buprenorphine treatment discontinuation prediction performance of machine learning models at first and second stage of treatment
Treatment stage for making prediction | Performance metrices | Decision tree | Random forest | Extreme gradient boosting | Logistic regression | Neural network | Support vector machine |
|---|---|---|---|---|---|---|---|
First stage models with baseline predictors | Precision | 0.57 ± 0.01 | 0.56 ± 0.02 | 0.53 ± 0.02 | 0.56 ± 0.02 | 0.56 ± 0.04 | 0.57 ± 0.03 |
Recall | 0.44 ± 0.02 | 0.49 ± 0.02 | 0.52 ± 0.03 | 0.38 ± 0.02 | 0.42 ± 0.05 | 0.38 ± 0.03 | |
F1 score | 0.49 ± 0.02 | 0.53 ± 0.02 | 0.52 ± 0.03 | 0.45 ± 0.01 | 0.47 ± 0.03 | 0.38 ± 0.02 | |
C-statistics | 0.58 ± 0.01 | 0.59 ± 0.02 | 0.55 ± 0.02 | 0.57 ± 0.02 | 0.57 ± 0.02 | 0.56 ± 0.02 | |
Second stage models with 2 months PDC* and baseline predictors | Precision | 0.66 ± 0.02 | 0.67 ± 0.02 | 0.58 ± 0.02 | 0.76 ± 0.02 | 0.67 ± 0.07 | 0.66 ± 0.03 |
Recall | 0.50 ± 0.04 | 0.55 ± 0.01 | 0.57 ± 0.02 | 0.37 ± 0.01 | 0.51 ± 0.12 | 0.52 ± 0.01 | |
F1 score | 0.57 ± 0.02 | 0.60 ± 0.01 | 0.58 ± 0.02 | 0.49 ± 0.01 | 0.55 ± 0.05 | 0.58 ± 0.01 | |
C-statistics | 0.67 ± 0.01 | 0.69 ± 0.01 | 0.63 ± 0.02 | 0.67 ± 0.02 | 0.67 ± 0.02 | 0.64 ± 0.01 | |
Second stage models with 3 months PDC* and baseline predictors | Precision | 0.67 ± 0.01 | 0.70 ± 0.02 | 0.62 ± 0.02 | 0.78 ± 0.03 | 0.72 ± 0.04 | 0.77 ± 0.06 |
Recall | 0.58 ± 0.04 | 0.59 ± 0.02 | 0.61 ± 0.01 | 0.44 ± 0.02 | 0.53 ± 0.03 | 0.44 ± 0.06 | |
F1 score | 0.63 ± 0.02 | 0.63 ± 0.02 | 0.61 ± 0.01 | 0.56 ± 0.02 | 0.61 ± 0.02 | 0.56 ± 0.04 | |
C-statistics | 0.71 ± 0.02 | 0.73 ± 0.02 | 0.68 ± 0.02 | 0.70 ± 0.02 | 0.70 ± 0.03 | 0.67 ± 0.02 |