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Sajad Mazaheri , Maryam Ashoori, Zeynab Bechari,
Volume 11, Issue 3 (9-2017)
Abstract

Background and Aim: Nowadays heart disease is very common and is a major cause of mortality. Proper and early diagnosis of this disease is very important. Diagnostic methods and treatments of the disease are so expensive and have many side effects. Therefore, researchers are looking for cheaper ways to diagnose it with high precision. This study aimed to identify a model for the treatment of heart disease.
Materials and Methods: In this descriptive cross-sectional study, the sampling method was census. The sample consisted of data from Khatam and Ali Ibn Abi Talib Hospitals in Zahedan. The data were developed as an Excel file, and Clementine12.0 software was used for data analysis. In the present study, C5.0, C & R Tree, CHAID, and QUEST algorithms and artificial neural network were carried out on the collected data. 
Results: The accuracy of 76.04 by C & R algorithm indicates the better performance of Decision Tree Algorithms than that of the Neural Network. 
Conclusion: This study aimed to provide a model for the prediction of a suitable heart disease treatment to reduce treatment costs and provide better quality of services for physicians. Due to considerable implementation risks of invasive diagnostic procedures such as angiography and also obtaining successful experiences of data analysis in medicine, this study has presented a model based on data analysis techniques. The improvable point of this model is the provision of a decision support system to help physicians to increase the accuracy of diagnosis in the treatment of diseases. 

Mohammad Mehdi Soltan Dallal, Reza Zandieh Moradi, Ramin Mazaheri Nezhad Fard, Zahra Rajabi,
Volume 13, Issue 5 (Dec & Jan 2020)
Abstract

Background and Aim: Transmission of pathogenic bacteria from animals to humans is possible directly or through the consumption of meat and milk or their products. The aim of this study was to identify and diagnose Enterohemorrhagic Escherichia coli (E. coli) by molecular method in cows' milk in Boroujerd city.
Materials and Methods: In a descriptive cross-sectional study, 150 milk samples were sampled from dairy farms in Boroujerd and its suburbs in four months from the beginning of November 2016 until the end of February 2017. After enrichment, culturing and biochemical tests on EMB agar and IMVIC differential tests, and doing linear culture on Sorbitol McConkey Agar medium to identify negative sorbitol isolates and confirm them by serological testing and eaeA gene identification, milk samples were analyzed by PCR test.
Results: Out of 31 isolates of Escherichia coli species, 6 were isolated as negative sorbitol (19.4%). Of these six isolates, five (16.1%) were identified as negative beta-galactosidase (MUG-) on chrome agar medium. In serological test, all 5 isolates were confirmed by O157: H7 antiserum antibody; besides, in molecular analysis, they had eaeA gene.
Conclusion: The outbreak of 16.1% of enterohemorrhagic E. coli in milk can be of great importance as one of the factors causing diarrhea in the community. Therefore, the outbreaks of consumption of this foodstuff in areas of the country that traditionally still put raw milk in food basket can provide valuable results for the prevention of diarrheal diseases.


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