Cone-beam computed tomography-based radiomic analysis of architectural phenotypes in jaw cysts and tumors using interpretable artificial intelligence models

Table 2 Non-redundant radiomic features retained following correlation pruning

Feature name	Domain	P value
Shape features
Voxel volume	Shape	0.026942
First-order features
Total energy	First-order	0.025882
Root mean squared	First-order	0.029218
Variance	First-order	0.032481
Maximum	First-order	0.045327
GLCM features
Difference variance	GLCM	0.024381
GLDM features
Dependence entropy	GLDM	0.026331
Dependence non-uniformity	GLDM	0.030004
Gray level variance	GLDM	0.033192
Gray level non-uniformity	GLDM	0.039126
GLRLM features
Run length non-uniformity	GLRLM	0.028417
Gray level variance	GLRLM	0.028963
Run entropy	GLRLM	0.027496
High gray level run emphasis	GLRLM	0.043527
GLSZM features
Gray level non-uniformity	GLSZM	0.027105
Zone entropy	GLSZM	0.035674
Large area high gray level emphasis	GLSZM	0.038415
Gray level non-uniformity normalized	GLSZM	0.041118
Gray level variance	GLSZM	0.044186
NGTDM features
Coarseness	NGTDM	0.025114
Complexity	NGTDM	0.040283

NGTDM: Neighborhood gray tone difference matrix; GLSZM: Gray level size zone matrix; GLRLM: Gray level run length matrix; GLDM: Gray level dependence matrix; GLCM: Gray level co-occurrence matrix.