Deep learning model combined with computed tomography features to preoperatively predicting the risk stratification of gastrointestinal stromal tumors

Table 2 Logistic regression analysis of risk classification based on clinical-imaging feature

	P value	95%CI
		Lower bound	Upper bound
Size	0.000	-0.763	-0.473
Range of tumor enhancement during the arterial phase	0.131	-0.035	0.005
Range of tumor enhancement during the venous phase	0.220	-0.007	0.032
Range of tumor enhancement during the delay phase	0.858	-0.021	0.017
Morphology	0.602	-0.387	0.608
Location	0.074	-0.063	1.386
Ulceration	0.004	-1.622	-0.300
Enlarged feeding vessels	0.000	-2.134	-1.094
Growth pattern	0.224	-0.833	0.328
Contrast enhancement during the venous phase	0.428	-2.266	1.384
Necrosis	0.236	-0.195	0,793
Lymph nodes	0.890	-1.934	1.678