scholarly journals Medical Information Mining-Based Visual Artificial Intelligence Emergency Nursing Management System

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Aihua Dong ◽  
Jian Guo ◽  
Yongzhi Cao
Keyword(s):  
Artificial Intelligence ◽  
Management System ◽  
Medical Information ◽  
First Aid ◽  
Emergency Nursing ◽  
Nursing Management ◽  
Hospital Emergency ◽  
Information Mining ◽  
Comparative Management ◽  
Query Management

This study aims to design a set of the visual artificial intelligence system based on medical information mining for hospital emergency care management. A visual artificial intelligence emergency first aid nursing management system is designed by analyzing the needs of the emergency first aid nursing management system. The results show that system personnel allocation, comparative management, record management, query management analysis, basic setup analysis, nursing management basis, and nonfunctional requirements all need to be optimized for the emergency first aid management system. In this study, the comparative management module, log management module, and the query management module are designed, and the emergency first aid management system of different APP terminal functions in different modules is described in detail. The nursing document query business is tested, and the corresponding time of query of nursing assessment sheet, nurse shift record, nurse record, and physical sign observation sheet is 375.50 ms, 351.48 ms, 336.36 ms, and 245.57 ms, respectively. It shows that the visual artificial intelligence emergency nursing management system based on medical information mining can provide convenience for clinical work to a large extent and has potential application value in hospital emergency nursing work.

Cardiological Database Management System as a Mediator to Clinical Decision Support

1996 ◽  
Vol 35 (01) ◽  
pp. 52-58 ◽  
Author(s):  
A. Mavromatis ◽  
N. Maglaveras ◽  
A. Tsikotis ◽  
G. Pangalos ◽  
V. Ambrosiadou ◽  
...  
Keyword(s):  
Management System ◽  
Database Management ◽  
Medical Information ◽  
Object Oriented ◽  
Medical Personnel ◽  
Database Management System ◽  
Ease Of Use ◽  
Medical Database ◽  
Analysis And Design ◽  
Object Oriented Design

AbstractAn object-oriented medical database management system is presented for a typical cardiologic center, facilitating epidemiological trials. Object-oriented analysis and design were used for the system design, offering advantages for the integrity and extendibility of medical information systems. The system was developed using object-oriented design and programming methodology, the C++ language and the Borland Paradox Relational Data Base Management System on an MS-Windows NT environment. Particular attention was paid to system compatibility, portability, the ease of use, and the suitable design of the patient record so as to support the decisions of medical personnel in cardiovascular centers. The system was designed to accept complex, heterogeneous, distributed data in various formats and from different kinds of examinations such as Holter, Doppler and electrocardiography.

Research on the framework of university ideological and political education management system based on artificial intelligence

2021 ◽  
pp. 1-10
Author(s):  
Xuying Sun ◽  
Yu Zhang
Keyword(s):  
Artificial Intelligence ◽  
Political Theory ◽  
Outlier Detection ◽  
Management System ◽  
Detection Algorithm ◽  
Colleges And Universities ◽  
Ideological And Political Education ◽  
Political Education ◽  
Data Simulation ◽  
Artificial Intelligence Technology

The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.

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