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Background: Based on the severity and prognostic condition of respective cancers caused by them, papilloma viruses are classified into high, medium, and low risk groups using E6 and E7 viral proteins. Nowadays, different methods of modeling in clinical medicine are used for diagnosis of diseases and evaluation of their molecular characteristics. Among the new methods of modeling, fuzzy systems are of particular importance in various fields of science. The aim of this study was to use a new intelligent Adaptive Nero Fuzzy Inference System (ANFIS) for predicting human papilloma virus oncogenicity based on a number of biochemical properties of E7 protein. Materials and Methods: In this study, using ANFIS model, a new model was developed for predicting oncogenicity of papilloma virus isolated from patients. The process of training and testing was performed using a set of available published filed data and several statistical and graphical criteria. Accordingly, through provision of needed biochemical and biophysical data on E7 gens from the existing data, this model was developed. The results of this model were, then, validated by the authentic published data. Results: Based on the results, the developed model is capable of predicting papilloma virus oncogenicity efficiently. R2 and RMSE values in training stage were 0.99 and 101.18, respectively. In the testing stage, however, they stood at 0.94 and 173.8, respectively. Conclusion: Based on the findings, the use of ANFIS model significantly improves the accuracy of estimating virus oncogenicity phenomenon. The methodology presented in this study is a new approach in estimating viral oncogenicity and can successfully be combined with other mathematical models for model updating in real conditions.

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Abstract

Background: Client satisfaction as an important indicator to assess the quality of provided services has found a special place over the past few decades. The main purpose of this study is to compare the client satisfaction in the public health posts and outsourced health posts affiliated to Qom university of medical Sciences in 2014.

Materials and Methods: This was a descriptive analytic (cross- sectional) study.The participants were 216 clients, who had referred to 10 public health posts and outsourced health posts of Qom province. Health posts  were selected by cluster sampling from different urban areas  and participants were selected by simple sampling methods. A researcher made questionnaire was used to measure the data on a 5-point Likert scale, which it's validity and reliability were confirmed by experts panel and Cronbach's alpha coefficient, respectively. After collection, the data were analyzed by SPSS 20, and descriptive statistical methods, Mann-Whitney test, chi-square, with 0.05 significant level.

Results: Among 60 health posts, 20 health posts (33.33%) were outsourced and 40 (66.66%) were managed by the public sector. Results showed that in health centers outsourced , overall satisfaction of the child care and vaccinations and maternity care were respectively, 64.5 and 55.42 and 67.43 percent and in public health posts were respectively, 35.5 and 44.58 and 37.66 percent and this difference was significant. Client satisfaction in the public health posts of the vaccination (57.1%) compared with client satisfaction in the outsourced health posts (47.2%) was higher, also at public health posts, satisfaction of the scientific skill employees (55.1 percent) assigned to the outsourced health posts (44.9%) was even greater, that this difference was significant.

Conclusion: Results of the present study showed that, there is a significant difference in satisfaction of clients in public health posts and outsourced health posts It seems necessary to pay special attention to employee training programs by managers and also considering the results of client satisfaction in performance appraisal of personnel in health care posts.