## 3 Results
### Biostatistics Analysis and Modeling Results  
The TMM (trimmed mean of M values) normalization approach was used to extract data from 16.386 lncRNAs in the dataset. In the study, 31 lncRNAs that may be associated with the disease state were selected using the Boruta variable selection method, one of the variable selection methods from lncRNAs that show different regulations (up and down), in order to reveal lncRNAs that may be associated with the disease state. Table 3 contains the selected expressions and dataset descriptions, the descriptors of the expressions chosen for the target variable under consideration, their statistical significance, the log fold change (LogFC) per gene for the target variable, and the data analysis results of these selected expressions. Figure 7: Volcano plot for the differentially expressed genes. Table 3 shows that statistically significant differences in lncRNA expression were identified between the rat group with nephrotoxicity and the control group for all lncRNA expressions except for rna-XR_005493563.1 (LOC120096731) (\(p<0.05\)). The findings of the performance metrics achieved as a result of the tree-based RF model using the selected lncRNAs are shown in Table 4.  
\begin{table}
\begin{tabular}{l l l l l l l l l} \hline \hline \multirow{2}{*}{**Gene Name**} & \multirow{2}{*}{**Chromosome**} & \multirow{2}{*}{**ID**} & \multicolumn{6}{c}{**Group**} \\ \cline{3-8}  & & & \multicolumn{2}{c}{**M**} & \multicolumn{2}{c}{**MK**} & \multirow{2}{*}{**LogFC**} & \multirow{2}{*}{\(p\)} \\ \cline{3-8}  & & & **Mean \(\pm\) SD** & \multicolumn{2}{c}{**Median**} & \multicolumn{2}{c}{**Mean \(\pm\) SD**} & \multicolumn{2}{c}{**Median**} & \multicolumn{2}{c}{**(Min-Max)**} & \\ \hline LOC120098190 & \multirow{2}{*}{NC\_051353.1} & ma- & \multirow{2}{*}{85.5 \(\pm\) 54.7} & 70 (9–172) & \multirow{2}{*}{19.5 \(\pm\) 18.58} & 16 (4–70) & 1.277 & 0.004 ** \\  & & & XR\_005496257.1 & & & & & \\ \hline LOC108348888 & \multirow{2}{*}{NC\_051354.1} & ma- & \multirow{2}{*}{71.2 \(\pm\) 32.64} & 75.5 (12–112) & \multirow{2}{*}{17.1 \(\pm\) 20.59} & 11.5 (3–74) & 1.250 & 0.002 ** \\ \hline LOC103691816 & \multirow{2}{*}{NC\_051338.1} & ma- & \multirow{2}{*}{210.4 \(\pm\) SD} & 230.5 (54–421) & \multirow{2}{*}{49.2 \(\pm\) 36.54} & 40.5 (19–147) & 1.171 & 0.001 ** \\ \hline LOC120098816 & \multirow{2}{*}{NC\_051355.1} & ma- & \multirow{2}{*}{220.6 \(\pm\) XR\_005497370.1} & 220.6 \(\pm\) 173.89 & 186 (48–552) & 31.3 \(\pm\) 22.35 & 30 (6–73) & 1.992 & 0.007 * \\ \hline LOC120096731 & \multirow{2}{*}{NC\_051349.1} & ma- & \multirow{2}{*}{6.6 \(\pm\) 6.64}  
The variable importance values of the expressions for the selected genes to explain the target variable (nephrotoxicity) are shown in Table 5.  
The variable importance values of the chosen lncRNAs used to explain the target variable. \begin{table}
\begin{tabular}{c c} \hline
**Metric** & **Value (\%) (95\% CI)** \\ \hline B-Acc & 88.9 (76.7–100) \\ \hline Acc & 90 (76.9–100) \\ \hline Sp & 90.9 (58.7–99.8) \\ \hline Se & 88.9 (51.8–99.7) \\ \hline Npv & 90.9 (58.7–99.8) \\ \hline Ppv & 88.9 (51.8–99.7) \\ \hline F1-score & 88.9 (75.1–100) \\ \hline \end{tabular}
\end{table} 
Table 4: The findings of the performance metrics achieved from the tree-based RF model. Figure 8: Graph of the performance metrics values for the RF model. \begin{table}
\begin{tabular}{c c} \hline
**Gene Name** & **Variable Importance Value** \\ \hline rna-XR\_591534.3 & 100 \\ \hline rna-XR\_005503408.1 & 80.127 \\ \hline rna-XR\_005495645.1 & 80.02 \\ \hline rna-XR\_001839007.2 & 47.205 \\ \hline rna-XR\_005492056.1 & 45.374 \\ \hline rna-XR\_351582.4 & 42.972 \\ \hline rna-XR\_001840278.2 & 42.9 \\ \hline rna-XR\_005496784.1 & 41.422 \\ \hline \end{tabular}
\end{table} 
Table 5: The variable importance values of the chosen lncRNAs used to explain the target variable.