jamal roohafza

Quality of life in people with thalassemia is impaired; thalassemia young adult cannot success in their life in society because of problems. This study investigated health-related quality of life of young adult with beta thalassemia major. This descriptive cross-sectional study was conducted on 55 young patients with thalassemia major referred to thalassemia center in hospital of Dezful. For assessment quality of life SF-36 questionnaire was used. Data analysis with SPSS-18 software using T-test, ANOVA, Pearson and Spearman correlation coefficient at significant level p<0.05 was used. A total of 55 young patients with thalassemia (33 males and 22 females) were enrolled. Mean of quality of life in these patients was 16.70±72.35. The average physical and mental health scores in these subjects were 76.27±16.03 and 69/99±19.44, respectively. The lowest and highest quality of life scores related to general health (61.68) and pain (85.86), respectively. Also in this study was found between general health and emotional well-being, there was a significant relationship with level of education (p>0.016). Positive correlation between income and pain was significant (p= 0.02) (r= 0.3). The results of this study demonstrated the quality of life of young adult with thalassemia in some aspects is not acceptable. Their physical and mental health should also be considered and so health systems should strive to improve the quality of life of these young people.

Today many people are likely to have diabetes. Diabetes is a serious disease of modern societies and its on-time diagnosis have important role in the treatment of disease.
In this paper, using Sugeno fuzzy inference systems and intelligent algorithms Firefly, a new method is presented for the detection of diabetes. The proposed method enables the use of a few simple fuzzy rules to detect diabetes with good accuracy.
Sugeno fuzzy inference system and firefly algorithm combines efficiency was 87.24 percent.
Experimental results show that this method deals on the data set is more accurate than the standard PID algorithm in this field.
bines efficiency was 87.24 percent. Experimental results show that this method deals on the data set is more accurate than the standard PID algorithm in this field.