Ethics code: IR.NKUMS.REC.1400.003
1- Master of Computer Engineering Software Orientation, Director of Statistics and Information and Communication Technology, North Khorasan University of Medical Sciences, Bojnurd, Iran , jheidarpour@nkums.ac.ir
2- Master of Computer Engineering Software Orientation, Management of statistics and information and communication technology, North Khorasan University of Medical Sciences, Bojnurd, Iran
3- Master of Computer Engineering majoring in software design and production, Management of statistics and information and communication technology, North Khorasan University of Medical Sciences, Bojnurd, Iran
4- Bachelor of Computer Engineering Software Orientation, Management of statistics and information and communication technology, North Khorasan University of Medical Sciences, Bojnurd, Iran
Abstract: (1377 Views)
Introduction: In the field of management, the statistics and performance of the deputies and functions of the organization are always of great importance, which requires instant access to the latest status of the system under coverage and minimal forecast of the future situation, to provide quality services Also improve. All of this justifies the existence of an intelligent statistical system with decision-making capabilities.
Methods: In this study, we try to create an integrated web-based system in order to electronicize the processes of defining and recording statistical information along with the aggregation of scattered data in the system and finally extract reliable knowledge from this data using modern artificial intelligence methods. In order to make decisions in the fields of health, treatment, medical education as well as health management. The intelligent management system of North Khorasan University of Medical Sciences has been designed and implemented under the web with the technique of making Webserver software & Learning & data mining in three phases for 48 months in PHP language and MySQL database.
Results: For this study, the statistical turnover structure of the university was classified into 1058 units. By classification based on the decision tree algorithm and reviewing the records of reports submitted to organizations at the same level and above, we reached 269833 units of data, 376 data types and 3885 data content. In the proposed method, the time cost of data transfer is less than one minute per item, and the required human resources due to the addition of multiple control sensors is 2640 people-hours per year, and significant time and financial savings were made.
Conclusions: According to the findings, it seems necessary to create a mechanized system for distribution, collection, control, analysis and reporting of statistical indicators that can have high accuracy and time and financial savings.
Type of Study:
Orginal Research |
Subject:
Basic Sciences Received: 2021/04/6 | Accepted: 2021/10/20 | Published: 2022/03/1