Development and Validation of a Random Forest Risk Prediction Pneumothorax Model in Percutaneous Transthoracic Needle Biopsy

10 December 2021 : Clinical Research

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

Background Material and Methods Results Discussion Conclusions References

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Table 5 Prediction performance of models on 15 vs 7 risk factors.

Models (AUC)	Development set		Delong test P value	Verification set		Delong test P value
Models (AUC)	15 risk factors	7 risk factors	Delong test P value	15 risk factors	7 risk factors	Delong test P value
LR	0.667	0.636	0.272	0.672	0.599	0.148
SVM	0.789	0.698	0.011	0.813	0.658	0.012
DT	0.792	0.789	0.815	0.825	0.814	0.632
RF	0.910^*	0.921^*	0.480	0.921^*	0.914^*	0.849
^* RF vs LR/SVM/DT (DeLong test, LR – logistic regression; SVM – support vector machine; DT – decision tree; RF – random forest; AUC – area under the curve.

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