## 3 Experimental Results and Discussion
### Multilayer CNN-Based Classifiers' Training and Validation
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Test Fold** & **Precision (\%)** & **Recall (\%)** & **Accuracy (\%)** & **F1 Score** \\ \hline \multirow{2}{*}{1} & 97.00 & 96.04 & \multirow{2}{*}{96.50} & \multirow{2}{*}{0.9652} \\  & (TP: 97, FP: 3) & (TP: 96, FN: 4) & & \\ \hline \multirow{2}{*}{2} & 95.00 & 95.00 & \multirow{2}{*}{95.50} & \multirow{2}{*}{0.9552} \\  & (TP: 96, FP: 4) & (TP: 96, FN: 5) & & \\ \hline \multirow{2}{*}{3} & 95.00 & 96.94 & \multirow{2}{*}{96.00} & \multirow{2}{*}{0.9596} \\  & (TP: 95, FP: 5) & (TP: 95, FN: 3) & & \\ \hline \multirow{2}{*}{4} & 95.00 & 95.96 & \multirow{2}{*}{95.50} & \multirow{2}{*}{0.9548} \\  & (TP: 95, FP: 5) & (TP: 95, FN: 5) & & \\ \hline \multirow{2}{*}{5} & 95.00 & 95.00 & \multirow{2}{*}{95.00} & \multirow{2}{*}{0.9500} \\  & (TP: 95, FP: 4) & (TP: 96, FN: 4) & & \\ \hline \multirow{2}{*}{6} & 96.00 & 96.00 & \multirow{2}{*}{96.00} & \multirow{2}{*}{0.9600} \\  & (TP: 96, FP: 4) & (TP: 96, FN: 4) & & \\ \hline \multirow{2}{*}{7} & 96.00 & 96.00 & \multirow{2}{*}{96.00} & \multirow{2}{*}{0.9600} \\  & (TP: 96, FP: 4) & (TP: 96, FN: 3) & & \\ \hline \multirow{2}{*}{8} & 96.00 & 96.97 & \multirow{2}{*}{96.50} & \multirow{2}{*}{0.9648} \\  & (TP: 96, FP: 4) & (TP: 96, FN: 4) & & \\ \hline \multirow{2}{*}{9} & 96.00 & 96.00 & \multirow{2}{*}{96.00} & \multirow{2}{*}{0.9600} \\  & (TP: 96, FP: 4) & (TP: 96, FN: 4) & & \\ \hline \multirow{2}{*}{10} & 97.00 & 97.00 & \multirow{2}{*}{97.00} & \multirow{2}{*}{0.9700} \\  & (TP: 97, FP: 3) & (TP: 97, FN: 3) & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Experimental results for 2D spatial and 1D CNN-based classifier with the 10-fold cross-validation test. Figure 10: Feature signals for tumor-free and tumor cases. (**a**) Tumor-free cases (100 Nors); (**b**) Tumor cases (50 Bs and 50 Ms). \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Test Fold** & **Precision (\%)** & **Recall (\%)** & **Accuracy (\%)** & **F1 Score** \\ \hline \multirow{2}{*}{1} & 97.00 & 96.04 & \multirow{2}{*}{96.50} & \multirow{2}{*}{0.9652} \\  & (TP: 97, FP: 3) & (TP: 96, FN: 4) & & \\ \hline \multirow{2}{*}{2} & 96.00 & 95.04 & \multirow{2}{*}{95.50} & \multirow{2}{*}{0.9552} \\  & (TP: 96, FP: 4) & (TP: 96, FN: 5) & & \\ \hline \multirow{2}{*}{3} & 95.00 & 96.94 & \multirow{2}{*}{96.00} & \multirow{2}{*}{0.9596} \\  & (TP: 95, FP: 5) & (TP: 95, FN: 3) & & \\ \hline \multirow{2}{*}{4} & 95.00 & 95.96 & \multirow{2}{*}{95.50} & \multirow{2}{*}{0.9548} \\  & (TP: 95, FP: 5) & (TP: 95, FN: 4) & & \\ \hline \multirow{2}{*}{5} & 95.00 & 95.00 & \multirow{2}{*}{95.00} & \multirow{2}{*}{0.9500} \\  & (TP: 95, FP: 5) & (TP: 95, FN: 5) & & \\ \hline \multirow{2}{*}{6} & 96.00 & 96.00 & \multirow{2}{*}{96.00} & \multirow{2}{*}{0.9600} \\  & (TP: 96, FP: 4) & (TP: 96, FN: 4) & & \\ \hline \multirow{2}{*}{7} & 96.00 & 96.00 & \multirow{2}{*}{96.00} & \multirow{2}{*}{0.9600} \\  & (TP: 96, FP: 4) & (TP: 96, FN: 4) & & \\ \hline \multirow{2}{*}{8} & 96.00 & 96.97 & \multirow{2}{*}{96.50} & \multirow{2}{*}{0.9648} \\  & (TP: 96, FP: 4) & (TP: 96, FN: 3) & & \\ \hline \multirow{2}{*}{9} & 96.00 & 96.00 & \multirow{2}{*}{96.00} & \multirow{2}{*}{0.9600} \\  & (TP: 96, FP: 4) & (TP: 96, FN: 4) & & \\ \hline \multirow{2}{*}{10} & 97.00 & 97.00 & \multirow{2}{*}{97.00} & \multirow{2}{*}{0.9700} \\  & (TP: 97, FP: 3) & (TP: 97, FN: 3) & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Experimental results for 2D fractional-order CNN-based classifier with the 10-fold cross-validation test.