# Prediction of Glioma Grades Using Deep Learning with Wavelet Radionic Features
## Appendix A  
In Table 11, the radiomic features considered in this study are listed. \begin{table}
\begin{tabular}{l l l l l} \hline \hline
**Number/Wavelet Group** & **Class** & **Feature** & **Mann-Whitney U Test** & **Evaluation** \\ \hline w1-LLH & First Order & Energy & \(p=0.004\) & \(p<0.05\) \\ w2-LLH & First Order & TotalEnergy & \(p=0.007\) & \(p<0.05\) \\ w3-LLH & GLDM & DependenceNonUniformity & \(p=0.000\) & \(p<0.05\) \\ w4-LLH & GLDM & GrayLevelNonUniformity & \(p=0.009\) & \(p<0.05\) \\ w5-LLH & GLDM & LargeDeconHigGrayLevelEmphasis & \(p=0.047\) & \(p<0.05\) \\ w6-LLH & GLDM & LowGrayLevelEmphasis & \(p=0.007\) & \(p<0.05\) \\ w7-LLH & GLDM & SmallDeconDeconGrayLevelEmphasis & \(p=0.000\) & \(p<0.05\) \\ w8-LLH & GLLRM & GrayLevelNonUniformity & \(p=0.005\) & \(p<0.05\) \\ w9-LLH & GLLRM & LongRunLowGrayLevelEmphasis & \(p=0.013\) & \(p<0.05\) \\ w10-LLH & GLLRM & LowGrayLevelRunEmphasis & \(p=0.007\) & \(p<0.05\) \\ w11-LLH & GLLRM & RunLengthNonUniformity & \(p=0.000\) & \(p<0.05\) \\ w12-LLH & GLLRM & ShortRunConGrayLevelEmphasis & \(p=0.005\) & \(p<0.05\) \\ w13-LLH & GLSLZM & GrayLevelNonUniformity & \(p=0.000\) & \(p<0.05\) \\ w14-LLH & GLSZM & LowGrayLevelZoneEmphasis & \(p=0.006\) & \(p<0.05\) \\ w15-LLH & GLSZM & SizeZoneNonUniformity & \(p=0.000\) & \(p<0.05\) \\ w16-LLH & GLSZM & SmallLevelonGrayLevelEmphasis & \(p=0.003\) & \(p<0.05\) \\ w17-LLH & GLSZM & ZoneEntropy & \(p=0.037\) & \(p<0.05\) \\ w18-LLH & NGTDM & Coarseness & \(p=0.000\) & \(p<0.05\) \\ w1-LRH & First Order & Energy & \(p=0.010\) & \(p<0.05\) \\ w2-LLH & First Order & TotalEnergy & \(p=0.017\) & \(p<0.05\) \\ w3-LLH & GLCM & Idmn & \(p=0.025\) & \(p<0.05\) \\ w4+HL & GLCM & Idn & \(p=0.036\) & \(p<0.05\) \\ w5-LLH & GLDM & DependenceNonUniformity & \(p=0.000\) & \(p<0.05\) \\ w6-LLH & GLDM & GrayLevelNonUniformity & \(p=0.005\) & \(p<0.05\) \\ w7-LLH & GLDM & LargeDeconHigGrayLevelEmphasis & \(p=0.016\) & \(p<0.05\) \\ w8-HL & GLDM & LowGrayLevelEmphasis & \(p=0.041\) & \(p<0.05\) \\ w9-LLH & GLDM & SmallDeconDeconGrayLevelEmphasis & \(p=0.001\) & \(p<0.05\) \\ w10-LLH & GLRLM & GrayLevelNonUniformity & \(p=0.002\) & \(p<0.05\) \\ w11-LLH & GLRLM & LowGrayLevelRunEmphasis & \(p=0.040\) & \(p<0.05\) \\ w12-LLH & GLRLM & RunningNonUniformity & \(p=0.000\) & \(p<0.05\) \\ w13-LLH & GLLRM & ShortRunLowGrayLevelEmphasis & \(p=0.029\) & \(p<0.05\) \\ w14-HL & GLSZM & GrayLevelNonUniformity & \(p=0.000\) & \(p<0.05\) \\ w15-LLH & GLSZM & LargeAreHighGrayLevelEmphasis & \(p=0.005\) & \(p<0.05\) \\ w16-LLH & GLSZM & LowGrayLevelZoneEmphasis & \(p=0.028\) & \(p<0.05\) \\ w17-LLH & GLSZM & SizeZoneNonUniformity & \(p=0.001\) & \(p<0.05\) \\ w18-LLH & GLSZM & SmallLevelonGrayLevelEmphasis & \(p=0.017\) & \(p<0.05\) \\ w19-LHL & NGTDM & Coarseness & \(p=0.000\) & \(p<0.05\) \\ w1-LHH & First Order & Energy & \(p=0.009\) & \(p<0.05\) \\ w2-LHH & First Order & TotalEnergy & \(p=0.016\) & \(p<0.05\) \\ w3-LHH & GLDM & DependenceNonUniformity & \(p=0.000\) & \(p<0.05\) \\ w4-LHH & GLDM & GrayLevelNonUniformity & \(p=0.004\) & \(p<0.05\) \\ w5-LHH & GLDM & LargeDeconHigGrayLevelEmphasis & \(p=0.023\) & \(p<0.05\) \\ w6-LHH & GLDM & SmallDependenceLowGrayLevelEmphasis & \(p=0.004\) & \(p<0.05\) \\ w7-LHH & GLRLM & GrayLevelNonUniformity & \(p=0.002\) & \(p<0.05\) \\ w8-LHH & GLRLM & RunLengthNonUniformity & \(p=0.000\) & \(p<0.05\) \\ w9-LHH & GLSZM & GrayLevelNonUniformity & \(p=0.000\) & \(p<0.05\) \\ w10-LHH & GLSZM & LargeAreHighGrayLevelEmphasis & \(p=0.012\) & \(p<0.05\) \\ w11-LHH & GLSZM & LowGrayLevelZoneEmphasis & \(p=0.043\) & \(p<0.05\) \\ w12-LHH & GLSZM & SizeZoneNonUniformity & \(p=0.003\) & \(p<0.05\) \\ w13-LHH & GLSZM & SmallLevelonGrayLevelEmphasis & \(p=0.025\) & \(p<0.05\) \\ w14-LHH & NGTDM & Coarseness & \(p=0.000\) & \(p<0.05\) \\ w1-LLL & GLCM & Idn & \(p=0.002\) & \(p<0.05\) \\ w2-LLL & GLCM & Idn & \(p=0.003\) & \(p<0.05\) \\ w3-LLL & GLCM & JointEntropy & \(p=0.023\) & \(p<0.05\) \\ w4-LLL & GLDM & DependenceEntropy & \(p=0.004\) & \(p<0.05\) \\ \hline \hline \end{tabular}
\end{table}