## 3 Results
### Aggregation Operators and q-ROFS  
Aggregation operators combined multiple experts' opinions. By applying these operators (Equations (26) and (30)) in Tables 2 and 3, a final table of patient symptoms was obtained. According to [PERSON]'s method, Equations (14) and (15) should be applied to calculate the table of membership and non-membership degrees. In addition, a value in q-rung is required because of q-ROFSs. By using relation value (Equation (18) or Equation (19)) or score and accuracy (Equations (20) and (21)), the final table of decision was calculated. Tables 12-31 show the results using aggregation operators and intuitionistic fuzzy sets (q = 1). Tables 32-51 show the results using aggregation operators and Pythagorean fuzzy sets (q = 2). Tables 52-71 show the results using aggregation operators and Fermatean fuzzy sets (q = 3). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Patient\textbackslash Disease**} & **Viral** & **Malaria** & **Typhoid** & **Stomach** & **Chest** \\  & **Fever** & **Fever** & **Fever** & **Problems** & **Problems** \\ \hline P\({}_{1}\) & 0.4000 & **0.7000** & 0.5100 & 0.0400 & 0.0612 \\ P\({}_{2}\) & 0.2000 & 0.0800 & 0.3822 & **0.6462** & 0.1602 \\ P\({}_{3}\) & 0.3500 & **0.6800** & 0.5700 & 0.0400 & 0.0500 \\ P\({}_{4}\) & 0.4000 & **0.7000** & 0.4400 & 0.2400 & 0.0960 \\ \hline \hline \end{tabular}  
* Patient P\({}_{1}\) suffered from malaria fever with score (0.700); patient P\({}_{2}\) suffered from stomach problems with score (0.65); patient P\({}_{3}\) suffered from malaria fever with score (0.6); patient P\({}_{4}\) suffered from malaria fever with score (0.65).  
\end{table} 
Table 18: Final decision with RV\({}_{2}\) (Aggregation: Harmonic Mean). \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Patient\textbackslash Disease**} & **Viral** & **Malaria** & **Typhoid** & **Stomach** & **Chest** \\  & **Fever** & **Fever** & **Fever** & **Problems** & **Problems** \\ \hline P\({}_{1}\) & 0.35, 0.45) & (**0.65, 0.75)** & (0.45, 0.65) & (-0.2, 0.6) & (-0.35, 0.75) \\ P\({}_{2}\) & \(\langle-0.2, 0.8)\) & (\(-\)0.4, 0.8) & (0.05, 0.85) & (**0.6, 0.7**) & (-0.55, 0.95) \\ P\({}_{3}\) & (0.3, 0.5) & (**0.6, 0.8**) & (0.5, 0.7) & (-0.2, 0.6) & (-0.3, 0.7) \\ P\({}_{4}\) & (0.4, 0.4) & (**0.7, 0.7**) & (0.2, 0.8) & (-0.06, 0.74) & (-0.16, 0.64) \\ \hline \hline \end{tabular}  
* Patient P\({}_{1}\) suffered from malaria fever with score (0.7); patient P\({}_{2}\) suffered from stomach problems with score (0.65); patient P\({}_{3}\) suffered from malaria fever with score (0.6); patient P\({}_{4}\) suffered from malaria fever with score (0.6); patient P\({}_{4}\) suffered from malaria fever with score (0.7).  
\end{table} 
Table 15: Score and Accuracy (Aggregation: Arithmetic Mean). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Patient\textbackslash Disease**} & **Viral** & **Malaria** & **Typhoid** & **Stomach** & **Chest** \\  & **Fever** & **Fever** & **Fever** & **Problems** & **Problems** \\ \hline P\({}_{1}\) & 0.4000 & **0.7000** & 0.5100 & 0.0400 & 0.0612 \\ P\({}_{2}\) & 0.2000 & 0.0800 & 0.3822 & **0.6462** & 0.1602 \\ P\({}_{3}\) & 0.3500 & **0.6800** & 0.5700 & 0.0400 & 0.0500 \\ P\({}_{4}\) & 0.4000 & **0.7000** & 0.4400 & 0.2400 & 0.0960 \\ \hline \hline \end{tabular}  
* Patient P\({}_{1}\) suffered from malaria fever with relation value (0.7000); patient P\({}_{2}\) suffered from stomach problems with relation value (0.6462); patient P\({}_{3}\) suffered from malaria fever with relation value (0.6800); patient P\({}_{4}\) suffered from malaria fever with relation value (0.7000).  
\end{table} 
Table 17: Final decision with RV\({}_{1}\) (Aggregation: Harmonic Mean).