• 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2020-03
  • 2020-07
  • 2020-08
  • 2021-03
  • Pain Skin changes Fatigue br Aggregated data


    Pain Skin changes Fatigue
    Aggregated data based on neutrosophic scale.
    Step 10. Begin to rank alternatives (diseases) using NSAW as follows:
    - Use five point scale which presented in Table 4 and construct decision matrix of alternatives according to each criterion. Aggregate experts opinions as we illustrated in step 7.
    - Use Eq. (4) to obtain crisp matrix of alternatives.
    - The normalized decision matrix must be calculated for posi-tive criteria as follows: xij
    and x−j is the smallest number of x in the column of j . But in our study we deal with positive criteria, since in case of having disease then the result is positive. So, we will use Eq. (5) in our study.
    and xij is the score of the i th alternative according to the j th criterion, wj is the weighted criteria.
    5. Application of proposed technique — a case study
    In this part we will complete the first part of proposed health-care system. Because the general symptoms of cancer may be similar to other existing diseases, we need to detect the disease that user is suffering from, if he/she does not have cancer according to proposed model of healthcare system. So we will apply the pro-posed (N-MCDM) technique for helping specialists and consultants to predict and detect which diseases that patient has a chance to be infected by it, and then advising him in an electronic healthcare record to go to the right specialist and out of the maze of disease. Here we will use the five linguistic variable scale for comparing the diverse elements of the subjects.
    By using the proposed health care system, the healthcare pro-fessionals founded that the user does not have cancer. But by analyzing obtained data from proposed healthcare system they founded that he M3814 (nedisertib) suffers from these symptoms: S = Fever, Weight loss, Pain, Skin changes, Fatigue . Thereafter, the specialists and consultants send a questionnaire to patient by email, for gathering more information about patient’s status. By obtaining question-naire’s answer they expected that the patient have one of these diseases: D = Typhoid, AIDS, Viral hepatitis . In order to determine the degree of association of each disease with patients’ symptoms do the following steps:
    Step 1. Select healthcare professionals who are specialists and consultants for helping in decision making.
    Predict patient’s disease
    Step 2. Construct the hierarchical structure of problem for simpli-fying directional selection as appears in Fig. 5.
    Step 3. Use the triangular neutrosophic scale which presented in Table 3 for constructing decision matrix of criteria according 
    Table 9
    Crisp matrix of diseases data.
    Normalized matrix of diseases data.
    The evaluation of diseases.
    Evaluation value
    Viral hepatitis
    to each expert opinion, and after that, aggregate all opinions of experts via using geometric mean as in Eq. (1). The aggregated matrix of experts is as in Table 5, since we have four specialists (experts) which aid in this case study: Step 4. Calculate weight of symptoms: The neutrosophic normalized matrix for decision matrix of symptoms as in Table 6.
    Then, take the average of each row in the normalized matrix of symptoms by using Eq. (3). then,
    Step 6. Use neutrosophic scale which presented in Table 4 and con-struct decision matrix of diseases according to criteria. After that aggregate experts matrices as we illustrated in proposed technique with detail. The aggregated matrix presented in Table 8.
    Step 7. Use Eq. (4) to obtain crisp matrix of alternatives (diseases) as presented in Table 9.
    Step 8. Construct normalized decision matrix by using Eq. (5). The normalized decision matrix of diseases presented in Table 10. Step 9. Begin to estimate each disease Ai via using Eq. (7). The result presented in Table 11.