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Introduction: Nowadays, electronic learning is not a choice but a necessity for higher education. This study aims at investigating readiness of faculty members of Iranian west medical universities in application of e-learning in learning processes. Materials & Methods: Running a stratified sampling technique, 140 faculty members of Iranian west medical universities were selected and their readiness for electronic learning application was assessed by a researcher-developed questionnaire. The reliability of the instrument turned out as acceptable using Cronbach’s Alpha coefficient. Hypotheses were tested utilizing t-test and one-way analysis of variance (ANOVA). Findings: Results of the study revealed that the respondents mostly believed in the effectiveness of e-learning environments in learning process. Further, those who had had abroad studies opportunities believed in the effectiveness of such environments, had knowledge and skill on these areas and used the environments more than others. Discussion & Conclusion: Providing opportunities for academic staff to experience learning and teaching process abroad and attending the e-learning conferences and workshops, especially for those who have been graduated more than ten years ago, would persuade them to utilize e-learning environments

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Abstract Introduction: Information Communication Technology (ICT) has been influential in all aspects of human life as in medical education. This study has been conducted with the aim of investigation of students’ skills and knowledge regarding working in e-learning environments, their belief in the effectiveness of these environments in learning, and their application of these environments. Materials & methods: Participants of this study were all medical sciences students in west universities in Iran that 370 students of them were selected as sample of the study. Instrument of the study was a questionnaire, developed by the researcher, which its reliability was turned out as acceptable by adopting Cronbach Alpha coefficient. Findings: The results of this study indicate that 69.5 percent of respondents at a medium level believe in the effectiveness of e-learning environments, knowledge and skill of 48.9 of respondents regarding working in these environments was low, 43 percent of respondents used such environments at a low level. Male respondents had more knowledge, skill and application of e-learning environments than female ones. Discussion & Conclusion: Inspired by the findings, it is recommended to investigate obstacles and elements confronting students in application of e-learning environments in medical universities from students’ viewpoints.

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Abstract

Introduction

Introduction

Data mining refers to the study and analysis of large amounts of data for discovering meaningful patterns and rules. Mainly through the models and algorithms, data mining puts the inputs in a specific order. Data mining techniques sometimes lead to the identification of meaningful algorithms which can use available and low-cost data in order to provide us with areas of infection, prevention, and treatment of diseases and help the physicians in timely and accurate diagnosis.

Materials & Methods

The present paper aimed to study the use of the results of data mining of hospital information systems by hospital managers for more accurate prediction and more effective decision-making about treatment of patients. The data used in this study included the information of 270 patients (14 variables) extracted from the database of UCI website. A “neural networks” model was used for the prediction of affliction with heart disease and its accuracy was measured and compared.

Research findings

According to the results, it can be observed that Multilayer Perceptron Neural Networks Model has classified the set of test observations with an accuracy of 83.33%.

Discussion & Conclusion

The results showed that the accuracy of “neural networks” model in classification of records in terms of heart disease response is 87.75% for the set of modeling records and 83.33% for the set of test records. In addition, the findings revealed that the variables of the number of large vessels (Nbr-ves), stress reduction (ST-dep), defect, chest pain, stress peak (Peak-ST), heart rate, angina, gender, age, static ECG (Res-elec), blood pressure (Blood-press), blood sugar, and serum cholesterol (Serum-chol), respectively, have the highest importance in “Multilayer Perceptron Neural Networks” model for the prediction of heart disease response.   

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Introduction: Heroin dependence is a chronic relapsing disorder caused by a combination of genetic, epigenetic, and environmental factors. The genetic contribution in the vulnerability to heroin dependence is 40%-60%. Alterations in dopamine transport in the CNS are implicated in drug and alcohol dependence, and according to linkage studies, the HTR2A rs6313 single nucleotide polymorphism plays an important role in drug dependence and abuse. This case-control study aimed to investigate the association between HTR2A rs6313 and heroin dependence among a population from Northwest Iran.
Material & Methods: The study included a sample of 100 heroin-dependent patients and 102 control subjects. After DNA extraction from blood samples, the genotype of HTR2A rs6313 polymorphism was investigated among patients and controls using the PCR-RFLP method. The obtained data were analyzed in SPSS software to explore a significant association.
(Ethic code: 5/4/12152)
Findings: Frequencies of CC, CT, and TT genotypes were 23%, 50%, and 27% in the patient group and 32.35%, 44.12%, and 23.53% in the control group. According to statistical analysis, there were no significant differences between case and control groups in this regard (P>0.05).
Discussion & Conclusion: The results of the study could not support a significant association between HTR2A rs6313 polymorphism and heroin dependence in the Azeri population of Northwest Iran. This indicates the need to investigate other candidate genetic polymorphisms in the study population.