Search published articles


Showing 2 results for Mirzaie
Human Resources Distribution Among Tehran University Of Medical Sciences Hospitals
Seyed Javad Ghazi Mirsaeid , Mahya Mirzaie , Elham Haghshenas , Hossein Dargahi ,
Volume 7, Issue 5 (1-2014)
Abstract

Background and Aim: Today, healthcare system is exposed to inappropriate human resources distribution challenges in all over the world. So far there is not an appropriate policy for human resources distribution in Iran. This deficiency may cause several problems for providing healthcare services. This research was aimed to determine the situation of human resources distribution among Tehran University Of Medical Sciences (TUMS) Hospitals.

Materials and Methods: This is a cross-sectional definitive study induced in four general and special TUMS hospitals. The research tool was a checklist that determine the number of nurses, paraclinic and supportive employees and finally the decrease and increased of the human resources among the departments of the hospitals regarding Iranian Ministry of Health (MOH) issues. The data was collected and analyzed by SPSS software and determined the differences between current situation in accordance to MOH issues.

Results: We observed the deficiency of human resources among all studied hospitals. Also the distribution of human resources among most of the hospitals departments was not coordinated with MOH issues.

Conclusion : It seems the distribution of human resources among Iranian healthcare system is not followed by a special model. Therefore, we suggest the model of health human resources planning should be determined and related by information, providers, services, education and policy as healthcare system factors and overlapping of these factors.


Determining the Effective Factors in the Incidence of Gastric Cancer by Using Data Mining Approach
Seyed Abbas Mahmoodi , Kamal Mirzaie, Seyed Mostafa Mahmoodi ,
Volume 11, Issue 3 (9-2017)
Abstract
Background and Aim: Gastric cancer is the second leading cause of cancer death in the world. Due to the prevalence of the disease and the high mortality rate of gastric cancer in Iran, the factors affecting the development of this disease should be taken into account. In this research, two data mining techniques such as Apriori and ID3 algorithm were used in order to investigate the effective factors in gastric cancer.
Materials and Methods: Data sets in this study were collected among 490 patients including 220 patients with gastric cancer and 270 healthy samples referred to Imam Reza hospital in Tabriz. The best rules related to this data set were extracted through Apriori algorithm and implementing it in MATLAB. ID3 algorithm was also used to investigate these factors.
Results: The results showed that having a history of gastro esophageal reflux has the greatest impact on the incidence of this disease. Some rules extracted through Apriori algorithm can be a model to predict patient status and the incidence of the disease and investigate factors affecting the disease. The prediction accuracy achieved through ID3 algorithm is 85.56 which was a very good result in the prediction of gastric cancer.
Conclusion: Using data mining, especially in medical data, is very useful due to the large volume of data and unknown relationships between systemic, personal, and Behavioral Features of patients. The results of this study could help physicians to identify the contributing factors in incidence of the disease and predict the incidence of the disease.

Page 1 from 1     

© 2024 , Tehran University of Medical Sciences, CC BY-NC 4.0

Designed & Developed by: Yektaweb