10 December 2021>: Clinical Research
Development and Validation of a Random Forest Risk Prediction Pneumothorax Model in Percutaneous Transthoracic Needle Biopsy
Hong Lin Wu 1ABCDEF , Gao Wu Yan 2ADF , Li Cheng Lei 3BC , Yong Du 4AD , Xiang Ke Niu 1DF , Tao Peng 1FG*DOI: 10.12659/MSM.932137
Med Sci Monit 2021; 27:e932137
Table 4 Prediction performance of models on 7 risk factors.
Models | Development set | Verification set | ||||||
---|---|---|---|---|---|---|---|---|
LR | SVM | DT | RF | LR | SVM | DT | RF | |
Sensitivity | 0.657 | 0.657 | 0.788 | 0.847 | 0.767 | 0.791 | 0.907 | 0.953 |
Specificity | 0.537 | 0.648 | 0.639 | 0.824 | 0.315 | 0.315 | 0.519 | 0.685 |
Accuracy | 0.604 | 0.653 | 0.722 | 0.837 | 0.515 | 0.526 | 0.691 | 0.804 |
PPV | 0.643 | 0.703 | 0.735 | 0.859 | 0.471 | 0.479 | 0.600 | 0.707 |
NPV | 0.552 | 0.598 | 0.704 | 0.809 | 0.630 | 0.654 | 0.875 | 0.949 |
PPV – positive predictive value; NPV – negative predictive value; LR – logistic regression; SVM – support vector machine; DT – decision tree; RF – random forest. |