# Health Symptom Checking System for Elderly People Using Fuzzy Analytic Hierarchy Process
## 3 Approach
### Weight Determination for Various Diseases  
To illustrate the cognitive response of the symptom checker with MCDA fuzzy AHP, we defined 9 linguistic variable scales of absolute numbers with triangular fuzzy scales to tag the relative preference based on the importance of the comparison of different elements of the subjects for validity and reliability of the assessment. The basic classifications of the fuzzy AHP assessment scale are equally important, weakly or slightly important, moderately important, moderately plus, strongly important, strongly plus, very strong, very very strong, extremely important, and also gave a measurement of 1 to 9 on the nominal scale. The meanings of each measurement with the fuzzy numbers associated with corresponding linguistic variables and TFNs [27] are described in Table 1. \begin{table}
\begin{tabular}{c c c c} \hline
**Linguistic Variables** & **Linguistic Scales** & **Triangular Fuzzy Scales** & **Fuzzy Reciprocal** \\ \hline Equally Important & 1 & (0.02, 0.18, 0.80) & (0.02, 0.18, 0.80) \\ Weakly or Slightly & 2 & (0.07, 0.23, 0.70) & (0.23, 0.07, 0.70) \\ Moderately Important & 3 & (0.13, 0.27, 0.60) & (0.27, 0.13, 0.60) \\ Moderately Plus & 4 & (0.22, 0.28, 0.50) & (0.28, 0.22, 0.50) \\ Strongly Important & 5 & (0.33, 0.27, 0.40) & (0.27, 0.33, 0.40) \\ Strongly Plus & 6 & (0.47, 0.23, 0.30) & (0.23, 0.47, 0.30) \\ Very Strong & 7 & (0.62, 0.18, 0.20) & (0.18, 0.62, 0.20) \\ Very Very Strong & 8 & (0.80, 0.10, 0.10) & (0.10, 0.80, 0.10) \\ Extremely Important & 9 & (1.0, 0, 0) & (0, 1, 0, 0) \\ \hline \end{tabular}
\end{table} 
Table 1: Linguistic variable scales of absolute value. Figure 4: Symptom checker interface of H2U. (**a**) Interface of H2U system; (**a**) Interface of H2U system; (**c**) Suggested disease. Considering healthcare problems, there are many factors that need to be taken into consideration. To illustrate the evaluation of the symptom checker, the 9 standard entities were taken to describe the level of match between the patient symptoms, S = {_chest pain_, _toothae_, _fever_, _thirst_, _weight loss_, _Blurred vision_, _dizziness_, _swelling_, _depression_} on the decision criteria, and the diseases, D = {_mental illness_, _diabetes_, _skin_, _eye_, _dental_, _ortho_, _cardiac_} as alternatives suffered by the elderly. Figure 5 shows a hierarchical structure of various attributes of criteria as _symptoms_ and alternatives as _diseases_ to set the goal for qualitative judgments verifying the prioritization of uncertainty decision [28; 29]. The hierarchical structure is a skeleton depiction of the system structure, and was used to study the interaction between various symptoms and their impact on the entire system. To measure the performance assessment, the system compares every possible relationship and dependency among the multiple options of symptoms chosen by the users. Then, the structure aggregates enough granularity of weights of importance to distinguish and deliver conceivable diagnoses of symptoms. The design operation of the symptom checker is shown in the following ways. Since there were 9 sets of criteria of symptoms from the case study, there could be 9 comparisons based on the criteria, creating a 9 \(\times\) 9 matrix. The diagonal elements of the matrix were always set to 1 and then the upper triangular matrix was filled up based on the importance of the alternatives as shown in Table 2.  
To fill the upper triangular matrix, the following rules were used [30]:  
* If the judgment value was on the left side of 1, the actual judgment value was inserted. * If the judgment value was on the right side of 1, the reciprocal value was inserted. To fill the lower triangular matrix, we used the reciprocal values of the upper diagonal.