## 3 Results
### Model Verification  
The coefficients of the regression model were calculated. All significantly changing variables (at the significance level of 0.05) are presented in Table 2.  
In case of the proposed model (Table 2), \(OR\) values that significantly deviate from value 1 were obtained for the current/past smoker attribute (\(OR=0.012\), 95% CI: \(0.001\div 0.023\)). This means that people who smoke more often suffer from CD. We can conclude that smoking does not affect the development of UC. Another attribute is blood in stool. In this case, \(OR=14.454\), 95% CI: \(14.324\div 14.658\), which means that the phenomenon of bloody stools much more often means UC than CD. The occurrence of blood stools increases the probability of UC by about 15 times.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Variable**} & \multirow{2}{*}{**Coefficient**} & \multirow{2}{*}{\(p\)**-Value**} & \multicolumn{3}{c}{**OR**} \\ \cline{3-6}  & & & & **Value** & **95\% CI (Low)** & **95\% CI (High)** \\ \hline Current/past smoker & \(-4.449\) & \(0.000\) ** & \(0.012\) & \(0.001\) & \(0.023\) \\ Blood in stool & \(2.671\) & \(0.000\) ** & \(14.454\) & \(14.324\) & \(14.658\) \\ MCV [\(f\)/L] & \(0.176\) & \(0.015\) * & \(1.913\) & \(1.899\) & \(2.101\) \\ PLT [\(x10^{3}\)/\(\mu\)L] & \(0.0002\) & \(0.019\) * & \(1.201\) & \(1.199\) & \(1.215\) \\ Neutrophphils [\(x10^{3}\)/\(\mu\)L] & \(-0.041\) & \(0.041\) * & \(0.96\) & \(0.94\) & \(1.11\) \\ Monocytes [\(x10^{3}\)/\(\mu\)L] & \(0.048\) & \(0.031\) * & \(1.049\) & \(1.039\) & \(1.149\) \\ Eosinophils [\(x10^{3}\)/\(\mu\)L] & \(0.096\) & \(0.004\) * & \(1.101\) & \(1.002\) & \(1.111\) \\ Basophils [\(x10^{3}\)/\(\mu\)L] & \(0.750\) & \(0.002\) * & \(2.118\) & \(2.018\) & \(2.128\) \\ AlAT [\(l\)/L] & \(0.029\) & \(0.001\) * & \(1.029\) & \(1.001\) & \(1.089\) \\ Creatinine [mg/dL] & \(-0.346\) & \(0.019\) * & \(0.708\) & \(0.698\) & \(0.798\) \\ Sodium [mmol/L] & \(0.149\) & \(0.000\) ** & \(1.162\) & \(1.142\) & \(1.182\) \\ Potassium [mmol/L] & \(-2.448\) & \(0.017\) * & \(0.086\) & \(0.077\) & \(0.096\) \\ Intercept & \(-23.877\) & \(0.006\) * & & & \\ \hline \hline \end{tabular}  
* significant at the level of \(\alpha=0.05\) ** significant at the level of \(\alpha=0.001\).  
\end{table}
Table 2: Coefficients with the \(p\)-value and odds ratio (OR).  
Figure 2: Distribution of data depending on the presence of smoking.  
In the case of MCV, \(OR\) = 1.913 (95% CI: 1.899 \(\div\) 2.101), which means that increasing its value should cause the patient to be classified into the group with UC disease. Similar results were obtained for PLT (\(OR\) = 1.201, 95% CI: 1.199 \(\div\) 1.215), monocytes (\(OR\) = 1.049, 95% CI: 1.039 \(\div\) 1.149), eosinophils (\(OR\) = 1.101, 95% CI: 1.002 \(\div\) 1.111), basophils (\(OR\) = 2.118, 95% CI: 2.018 \(\div\) 2.128), ALAT (\(OR\) = 1.029, 95% CI: 1.001 \(\div\) 1.089), and sodium (\(OR\) = 1.162, 95% CI: 1.142 \(\div\) 1.182). In the case of neutrophils, \(OR\) = 0.96 (95% CI: 0.94 \(\div\) 1.11), and increasing their value should cause the patient to be classified into the group with CD disease. Similar results were obtained for creatinine (\(OR\) = 0.708, 95% CI: 0.698 \(\div\) 0.798) and potassium (\(OR\) = 0.086, 95% CI: 0.077 \(\div\) 0.096) (Table 2).  
The measurements characterizing the constructed model concerning IBD diseases were calculated (Table 3). The sensitivity value is 0.84 for specificity 0.74. The AUC was 0.93 (Figure 3). The proposed AQM measure also indicates a good prediction quality, as AQM = 0.79.