# Predicting the Survival of Primary Biliary Cholangitis Patients
## 4 Discussion
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \# & **DMT** & **S** & **SM** & **MVA** & **DA** & **Accuracy** & **Precision** & **Sensitivity** & **Specificity** & **AUC** \\ \hline
1 & DT & S1 & SV (0.7) & MVA1 & DA1 & 85.60\% & 84.71\% & 93.51\% & 72.92\% & 0.855 \\ \hline
2 & DT & S1 & SV (0.8) & MVA1 & DA1 & 89.16\% & 88.89\% & 94.12\% & 81.25\% & 0.500 \\ \hline
3 & RF & S1 & SV (0.8) & MVA1 & DA1 & 92.77\% & 95.92\% & 92.16\% & 93.75\% & 0.849 \\ \hline
4 & RT & S1 & SV (0.8) & MVA1 & DA1 & 85.54\% & 85.45\% & 92.16\% & 75.00\% & 0.688 \\ \hline
5 & DT & S1 & SV (0.8) & MVA2 & DA1 & 89.09\% & 88.57\% & 93.94\% & 81.82\% & 0.826 \\ \hline
6 & RF & S1 & SV (0.8) & MVA2 & DA1 & 94.55\% & 91.67\% & 100\% & 86.36\% & 0.884 \\ \hline
7 & RF & S1 & SV (0.8) & MVA1 & DA2 & 93.14\% & 90.74\% & 96.08\% & 90.20\% & 0.975 \\ \hline
8 & RF & S1 & SV (0.8) & MVA1 & DA3 & 93.75\% & 91.18\% & 96.88\% & 90.62\% & 0.967 \\ \hline
9 & RF & S2 & SV (0.8) & MVA1 & DA1 & 93.98\% & 91.07\% & 100\% & 84.38\% & 0.946 \\ \hline
10 & RF & S3 & SV (0.8) & MVA1 & DA1 & 92.77\% & 90.91\% & 98.04\% & 84.38\% & 0.968 \\ \hline
11 & RF & S4 & SV (0.8) & MVA1 & DA1 & 90.36\% & 92.16\% & 92.16\% & 87.50\% & 0.825 \\ \hline
12 & RF & S2 & SV (0.8) & MVA1 & DA3 & 89.16\% & 87.50\% & 96.08\% & 78.12\% & 0.871 \\ \hline
13 & RF & S3 & SV (0.8) & MVA1 & DA3 & 93.75\% & 88.89\% & 100\% & 87.50\% & 0.954 \\ \hline
14 & RF & S4 & SV (0.8) & MVA1 & DA3 & 95.31\% & 96.77\% & 93.75\% & 96.88\% & 0.906 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Best results obtained regarding Accuracy, Precision, Sensitivity, Specificity, and AUC value. results in values superior to 90%, which are also promising results, but not as high as the ones obtained in attempts 12 and 14. Additionally, comparing attempts 12 and 13, increasing the threshold value, from 0.05 (S2) to 0.1 (S3), was not beneficial to the results, and the removal of five more attributes in the S3 scenario, although resulting in a Sensitivity value of 100%, slightly reduced the percentage values of all the other metrics, subsequently implying a slight loss in predictive power in attempt 13. Looking now specifically to attempt 12, it is still possible to interpret each one of the obtained metrics. Therefore: its 95.31% accuracy value demonstrates that this model correctly predicted almost every patient's status (survival or non-survival); its 96.77% precision value is related to the correctly predicted positive values, where this elevated value allows us to infer that there were only a few FP values in the calculated model, thus revealing that only a small fraction of deceased patients (status = 1) were predicted to have survived (status = 0); its 93.75% sensitivity value, as already mentioned, gives information about how many patients were correctly labelled as 1 (non-surviving) of those who were initially described as 1 in the dataset, meaning that, since this value is superior to 90%, the survival of many non-survival patients was not incorrectly predicted (low FN); its 96.88% specificity value, as said before, provides how many patients were correctly labelled as 1 (not survived) of the initial deceased patients, where this high value allows us to infer that the survival of many patients that were actually deceased was not incorrectly predicted. Lastly, its 0.990 AUC value is also vital to show that this model is close to the \"perfect\" classifier (that has an AUC value equal to 1), which means that this model has the ability to correctly distinguish the classes of the status attribute, fittingly predicting almost all 0 s as 0 s and 1 s as 1 s. Although promising results have been achieved, a direct comparison cannot be performed because the studies mentioned in the Related Work focus on the analysis of treatments for PBC rather than specifically on its prognosis or evolution.