## 4 Experimental Results and Discussion
### Statistical Analysis of Data
#### 4.1.3 Model 3: Estimation of the Tumor Recurrence Variable Using the Two-State Logit Model  
The results of the two-state logit model estimation for predicting tumor recurrence in patients are presented below. The mathematical model incorporates the dependent variable \"tumor recurrence\" and the independent variables that affect this variable.  
\[\begin{array}{l}Tumor\ Recurrence=0.0722-(0.0064*donor\ size)+(0.0028*primary\ tumor\ size)+\\ (0.2672*number\ of\ tumors)-(0.0244*tumor\ diameter2)+(0.5132*tumor\ location5)-(0.1709*hepatic\ status)-(0.0052* pathology\ tumor\ diameter1)+(0.0065*pathology\ tumor\ diameter2)+(0.7931*ht)\end{array}\]  
The interpretation of the model will be made according to the odds ratio (OR) values. Accordingly, a statistically significant relationship was found between donor size and tumor recurrence. According to the results of odds ratios, it was determined that there was a decrease towards the category of \"patient has tumor and recurrence\" as the donor size value was increased (OR = 0.993; \(p<0.01\)). Similarly, a statistically significant relationship was found between the primary tumor size and tumor recurrence. According to the results of the odds ratios, it was determined that there was an increase towards the category of \"patient has tumor and recurrence\" as the primary tumor size was increased (OR = 1.003;\(p<0.01\)). A statistically significant relationship was found between the number of tumors and tumor recurrence. Accordingly, it was determined that as the number of tumors increased, there was an increase in the patient tumor and recurrence category (OR = 1.306; \(p<0.01\)). A statistically significant relationship was found between tumor diameter 2 and tumor recurrence. Accordingly, it was determined that there was a decrease towards the category of \"the patient has tumor and recurrence\" as the tumor diameter 2 variable was increased (OR = 0.975; \(p<0.01\)). A statistically significant relationship was detected between the tumor location 5 variable and tumor recurrence. According to the results of the betting odds ratios, it was determined that there was a decrease towards the category \"the patient has tumor and recurrence\" as the tumor location 5 was increased (OR = 1.671; \(p<0.05\)). Similarly, a statistically significant relationship was found between the hepatic status variable and tumor recurrence. As the hepatitis status variable was increased, there was a decrease towards the category of \"the patient has tumor and recurrence\" (OR = 0.843; \(p<0.01\)). A statistically significant relationship was found between the pathology tumor diameter 1 variable and tumor recurrence. As the pathology tumor diameter 1 increased, it was determined that there was a decrease towards the category of \"the patient has tumor and recurrence\" (OR = 0.995; \(p<0.05\)). Similarly, a statistically significant relationship was found between the pathology tumor diameter 2 variable and tumor recurrence. As the pathology tumor diameter 2 increased, there was an increase towards the category of \"the patient has tumor and recurrence\" (OR = 1.007; \(p<0.05\)). A statistically significant relationship was found between the Ht variable and tumor recurrence. Accordingly, it was determined that as Ht increased, there was an increase towards the category of \"the patient has tumor and recurrence\" (OR = 2.210; \(p<0.01\)).