Data Mining technology as a tool for supporting analytical decision making process in Health Information Management System (HIMS)

2021 ◽  
Vol 5 (2) ◽  
pp. 139-147
Author(s):  
Gbenga Femi Asere ◽  
Dung Emmanuel Botson
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Information System ◽  
Strategic Management ◽  
Information Management ◽  
Management System ◽  
Clinical Decision Making ◽  
Information Management System ◽  
Decision Making Process ◽  
Mining Technology

Wide spread use of information system in the delivery of managed healthcare system and the challenges of identifying and disseminating relevant healthcare information, complex and diverse data and knowledge forms and tasks coupled with the prevalence of legacy systems require automated approaches for effective and efficient utilization of massive amount of data to support in strategic planning and decision-making and assist the strategic management mechanisms. Despite the fact that data mining is progressively used in information systems as a technology to support analytical decision making, it is however still barely used in hospital information system to support analytical decision making process. Hence, this paper presents the usefulness of data mining technology in Hospital Information Management System (HIMS). Data mining technology offered capabilities to increase the productivity of medical personnel, analyze care outcomes, lower healthcare costs, improve healthcare quality by using fast and better clinical decision making and generally assist the strategic management mechanisms.

The Application of Data Mining Technology in the Remote Open Management System

2014 ◽  
Vol 687-691 ◽  
pp. 1141-1144
Author(s):  
Mei Bai
Keyword(s):  
Data Mining ◽  
Quality Assessment ◽  
Information Management ◽  
Management System ◽  
Information Management System ◽  
Assessment System ◽  
Detailed Design ◽  
Mining Technology ◽  
Open Management ◽  
At Home

This paper introduces the concept of database and data mining, combined with management system of quality assessment system and method of data mining technology. In this paper, applying the data mining skill to the field of remote open management system, introduces the development of data mining in China and the necessity and importance of data mining in remote open information management system. This thesis analyzes the main problems in the remote open management system. On the basis of the relevant researches both at home and abroad, it presents the significance of the application of data mining in remote open management system. It analyzes the needs of the system based on data mining and presents a detailed design and implication of such a system.

Study on Data Mining with Decision Tree Algorithm in the Student Information Management System

2014 ◽  
Vol 543-547 ◽  
pp. 3602-3605
Author(s):  
Liang Li ◽  
Ying Zheng ◽  
Xiao Hua Sun ◽  
Fu Shun Wang
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Information Management ◽  
Management System ◽  
Information Management System ◽  
Decision Tree Algorithm ◽  
Mining Technology ◽  
Tree Algorithm ◽  
Student Information ◽  
Decision Tree Method

With the advance of education informationization in china, information technology and data mining technology has been widely used in the field of education. The decision tree method is one of the data mining methods; it does not require any assumption, can intelligent classification to a large amount of data directly. According to certain rules to find hidden and valuable information.Use the idea of learners as the center as guiding principle, using decision tree algorithm of data mining technology to build student information management system, selects typical C4.5 algorithm among the decision tree methods, Take mass information about employment of graduation in university students' information management system as an example to generate the decision tree, collect potential rules and factors in favor of graduat employment, so as to guide the education and management.

scholarly journals Construction of Student Information Management System Based on Data Mining and Clustering Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
XueHong Yin
Keyword(s):  
Data Mining ◽  
Genetic Algorithm ◽  
Information Management ◽  
Management System ◽  
Clustering Algorithm ◽  
Student Evaluation ◽  
Information Management System ◽  
Fuzzy Genetic Algorithm ◽  
Student Information ◽  
Fuzzy Genetic

Data mining is a new technology developed in recent years. Through data mining, people can discover the valuable and potential knowledge hidden behind the data and provide strong support for scientifically making various business decisions. This paper applies data mining technology to the college student information management system, mines student evaluation information data, uses data mining technology to design student evaluation information modules, and digs out the factors that affect student development and the various relationships between these factors. Predictive assessment of knowledge and personalized teaching decision-making provide the basis. First, the general situation of genetic algorithm and fuzzy genetic algorithm is introduced, and then, an improved genetic fuzzy clustering algorithm is proposed. Compared with traditional clustering algorithm and improved genetic fuzzy clustering algorithm, the effectiveness of the algorithm proposed in this paper is proved. Based on the analysis system development related tools and methods, in response to the needs of the student information management system, a simple student information management system is designed and implemented, which provides a platform and data source for the next application of clustering algorithm for performance analysis. Finally, clustering the students’ scores with a clustering algorithm based on fuzzy genetic algorithm, the experimental results show that this method can better analyze the students’ scores and help relevant teachers and departments make decisions.

scholarly journals Optimization of Clinical Nursing Management System Based on Data Mining

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yongxia Chen
Keyword(s):  
Data Mining ◽  
Information System ◽  
Information Management ◽  
Management System ◽  
Clinical Care ◽  
Nursing Management ◽  
Mining Technology ◽  
Clinical Nursing ◽  
Medical Order ◽  
Nursing Information System

The clinical nursing work based on the establishment and improvement of the clinical nursing system breaks through the traditional nursing work model, which has achieved the advantages of full traceability, practical operation, comprehensive analysis, and individual error correction of nursing work, and greatly improves the nursing quality and work efficiency of nurses. With the advent of the era of big data, how to organically combine data mining technology with nursing information to optimize the nursing information system, apply big data to clinical nursing work through nursing information system, and provide patients with more efficient, high-quality, and safe nursing services is a problem that needs urgent consideration in today’s era. Therefore, this research is based on the framework of the hospital’s existing clinical care system, using data mining technology to improve the Bayesian algorithm and data preprocessing, optimizes the design of functional modules in the clinical nursing management system, and optimizes the patient information management, medical order management, medical order execution management, basic information and expense management, nursing execution process management, system and data management, barcode management, physical sign management, WAP information management, and other subsystems in the clinical nursing information management system. Experiments have proved that the use of a data mining-based clinical care management system can simplify user operations and improve users’ application of software. The application system of nursing methods based on data mining technology more completely integrates nursing information management business, makes nursing information management initially “digital,” and can improve the quality of hospital care to a large extent.

A Research of Information Management System Based on Data Mining

2014 ◽  
Vol 513-517 ◽  
pp. 616-619 ◽  
Author(s):  
Ji Kun Wang ◽  
Xing Zhi Hu ◽  
Xue Zhe Li ◽  
Fei Ji Ding
Keyword(s):  
Data Mining ◽  
Information Management ◽  
Management System ◽  
Information Management System ◽  
University Management ◽  
Practical Applications ◽  
Reference Information ◽  
Information Management Systems ◽  
The University ◽  
Guidance Information

As it's known to all, taking full advantage of useful information in university information management systems can improve the quality and efficiency of university management. With the aim at the characteristic of the information management system, this paper proposes practical applications of the Data Mining in university information management by analyzing the process, main workload and main technical methods of data mining. And finally, we provide some guidance information and reference information for the university management staffs to help them accomplish the university management quickly and efficiently.

scholarly journals Data Mining Technology in Book Copyright Information Management Decision System

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Song Lifang
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Information Management ◽  
Association Rule ◽  
Information Management System ◽  
Management Decision ◽  
Apriori Algorithm ◽  
Mining Technology ◽  
Copyright Information ◽  
Rule Method

Today is an era of data “big bang”; Internet information technology is widely used in various fields of society. As an indispensable spiritual food in people’s daily life, books are increasing in number and scale. In order to better manage book information, people have introduced data mining technology. Based on this, this article takes the research and application of data mining technology in book copyright information management decision-making system as the theme, explores the role of data mining technology in book copyright information management, and aims to provide reference for our country’s book copyright information management and decision-making. This article first introduces the common algorithms of data mining technology and then elaborates on the advantages and effectiveness of the association rule method in data mining. Aiming at some defects of the original Apriori algorithm of the association rule method, an improved Apriori algorithm is proposed. After taking the library book information management system and database of a university in our province as the experimental research object, the performance gap between the two algorithms is compared through experiments, and it is concluded that when the number of transaction set item records is less than 1400, the Apriori algorithm performs better, and when the number of records in the transaction set is greater than 1400, the improved Apriori algorithm is obviously more advantageous. The research results show that the introduction and application of data mining technology make the information management of books more efficient and convenient, and it is more convenient for the management and decision-making of book copyright information.

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