Mohsen Askarishahi, Mehdi Mokhtari, Hasan Ashrafzadeh, Mehrzad Ebrahemzadih,
Volume 7, Issue 4 (Oct-Dec 2018)
Abstract
Introduction: Air pollution is now one of the greatest environmental hazards to human health in the world. The aim of this study determines the relationship between air quality and cases of myocardial infarction in Yazd.
Methods: This Ecological study was performed in Yazd, Iran. In this study, all individuals who referred to emergency cases with myocardial infarction in Yazd in one year from 2016 march 20 to 2017 March 20 entered the study. Information on daily concentration of air pollutants, including five pollutants SO2, CO, O3, NO2 and PM10 and Validated according to the World Health Criteria. And in the next step Raw data from air pollutants related to each station Using equation and table standard Converts to separate AQI values for each pollutant And the pollutant having the highest index It was introduced as a pollutant responsible for the day.The data analyzes were used by Excel 2007 and R (3.4.3) software. The significant level was considered to be less than 0.05.
Results: According to measurements of air pollutants, 349 days in 245 days, the standard air quality index (AQI <100) and 104 days a year above the standard standard (AQI> 100) were observed In 86 days, from 104 days PM10 and CO emissions as pollutants was responsible for introducing.
Conclusion: Given that in 104 days of the year, air quality has exceeded the standard In the days when air quality exceeds the standard, children and elderly take caution.
Amin Karami, Mohsen Askarishahi, Nasim Namiranian,
Volume 11, Issue 3 (9-2022)
Abstract
Introduction: Diabetes is one of the most common diseases caused by metabolic disorders. It is the result of impaired secretion or function of insulin. The prevalence of diabetes is increasing rapidly. The aim of this study is to investigate the performance of different decision tree algorithms in the diagnosis of diabetic retinopathy. It was done using a database regarding diabetic patients. They were referred to Yazd Diabetes Research Center.
Method: This study was analytical cross-sectional. 2613 patients visited Yazd City's research and treatment center. Their demographic information was received in the first stage. Then, they were tested by the nursing team, and the patient's information form was completed by the respective nurse. After that, the descriptive indicators of mean, mode, median, variance, frequency, and percentage of missing data were observed. Four diagnostic models (Chadi), classification tree and regression (C and R), (Quest) and C 5.0 were compared. Authors evaluated the performance of these four models using three statistical criteria: accuracy, sensitivity, and specificity. Gains chart was used for more accurate comparison of models. SPSS MODELER V 18.0 software was used for data processing and modeling. The significance level was considered 5%.
Result: In this study, among the demographic and clinical variables, BMI, duration of disease, type of drug used, age, hypertension, gender, cholesterol, and hemoglobin A1c were entered in the final model. The dependent variable of retinopathy was investigated. It was based on the obtained criteria of accuracy (71.75), sensitivity (75.60), specificity (57.14) in the CART model; accuracy (65.84), sensitivity (65.86), specificity (65.76) of the Quest model; accuracy (69.33), sensitivity (67.35), specificity (76.81) of Chaid model; and accuracy (73.27), sensitivity (79.65), specificity (49.05) of Chaid model.
Conclusion: Based on the criteria of accuracy, sensitivity, specificity, and comparison of Gain Chart for four algorithms, Chaid algorithm showed better performance. Therefore, for further research, the authors suggest this algorithm
