## 3 Results
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**mRMR** & & **ReliefF (k = 3)** \\ \hline \(\Delta\)**Variable** & **Variable Type** & \(\Delta\)**Variable** & **Variable Type** \\ \hline \begin{tabular}{c} Perfusion Abnormality in Left \\ Middle Temporal Gyrus \\ \end{tabular} & \begin{tabular}{c} Perfusion Abnormality \\ Temporal Pole \\ \end{tabular} & \begin{tabular}{c} NAP-2 \\ \end{tabular} & \begin{tabular}{c} Platelet Activation Marker \\ \end{tabular} \\ \hline \begin{tabular}{c} Perfusion Abnormality in \\ Right Brodmann Area (BA) 6 \\ \end{tabular} & \begin{tabular}{c} Perfusion Abnormality in \\ Inferior Temporal Gyrus \\ \end{tabular} & \begin{tabular}{c} Perfusion Abnormality in \\ Perfusion Abnormality \\ \end{tabular} \\ \hline \begin{tabular}{c} Perfusion Abnormality in \\ Right BA 23 \\ \end{tabular} & \begin{tabular}{c} Perfusion Abnormality \\ \end{tabular} & \begin{tabular}{c} ASTLCMD \\ \end{tabular} & \begin{tabular}{c} CANTAB: attention task \\ \end{tabular} \\ \hline \
\begin{tabular}{c} Thyroid-Stimulating \\ Hormone (TSH) \\ \end{tabular} &
\begin{tabular}{c} Functional Blood Test \\ \end{tabular} & Phosphorus & Metabolic Blood Test \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Five most distinct placebo vs. rosuvastatin non-behavioral features selected by the two feature selection techniques. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Sidak’s Multiple Comparison Test** & **Adjusted \(p\) Value** & **95\% Confidence Interval** \\ \hline \begin{tabular}{c} **Rosuvastatin** \\ HAM21 Before vs. HAM21 After \\ HAM17 Before vs. HAM17 After \\ BID-II Before vs. \\ BDI-II Before vs. \\ BDI-II After \\ \end{tabular} & \begin{tabular}{c} 0.0036 \\ 0.0006 \\ \end{tabular} & \begin{tabular}{c} 2.693–29.31 \\ 3.963–28.04 \\ 9.508–33.58 \\ 9.508–33.58 \\ \end{tabular} \\ \hline \begin{tabular}{c} **Placebo** \\ HAM21 Before vs. HAM21 After \\ HAM17 Before vs. HAM17 After \\ BDI-II Before vs. \\ BDI-II After \\ \end{tabular} & \
\begin{tabular}{c} 0.0025 \\ 0.0128 \\ 0.251 \\ \end{tabular} &
\begin{tabular}{c} 3.026–29.64 \\ 1.375–26.62 \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Statistical differences in mood before and after the study. 23 located in the medial region of the posterior cingulate gyrus, and plastic levels of thyroid-stimulating hormone (TSH). On the other hand, the features chosen by the Relieff algorithm included levels of sCD40L and NAP-2 (both peripheral platelet activation markers), perfusion abnormality in the left inferior temporal gyrus, ASTLCMD (a CANTAB variable that measures the median latency of response from stimulus appearance to button press in the system's attention switching task), and serum phosphorus levels. The highest average accuracy obtained by training classifiers over 20 iterations with the mRMR algorithm's selected features was 78.33% with the coarse tree classifier. The confusion matrix and the ROC curve (AUC value = 0.75) for one of the 20 iterations of the coarse tree classifier is shown in Figure 4a,b, respectively. This iteration was the closest to the average in terms of its accuracy value of 76.19%. Additionally, the percentage values of sensitivity, specificity, precision, FOR, and MCC for this iteration are shown in Table 5.  
Finally, the highest accuracy obtained by training the 25 different classifiers over 20 iterations with the features selected by the Relieff algorithm was 86.67%. The classifier that reported this accuracy was the weighted KNN classifier. The iteration for the weighted KNN classifier closest to the average value had an accuracy of 85.71%, and its confusion matrix with the ROC curve (AUC value = 0.93) are shown in Figure 4c,d, respectively.