A knowledge-driven decision support system for remote medical management

Yuqing Lu; Yuqing Lu

doi:10.3934/mbe.2023128

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 2: 2732-2749. doi: 10.3934/mbe.2023128

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Research article Special Issues

A knowledge-driven decision support system for remote medical management

Yuqing Lu ^{1,2
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1.
College of Economics and Business Administration, Cheongju University, Cheongju 28503, Chungbuk, Republic of Korea
2.
College of Social Sciences, Cheongju University, Cheongju 28503, Chungbuk, Republic of Korea

Academic Editor: Man-Fai Leung

Received: 27 September 2022 Revised: 02 November 2022 Accepted: 07 November 2022 Published: 28 November 2022

Residential medical digital technology is an emerging discipline combining computer network technology and medical research. Based on the idea of knowledge discovery, this study was designed to construct a decision support system for remote medical management, analyze the need for utilization rate calculations and obtain relevant modeling elements for system design. Specifically, the model constructs a design method for a decision support system for the healthcare management of elderly residents through the use of a utilization rate modeling method based on digital information extraction. In the simulation process, the utilization rate modeling and system design intent analysis are combined to obtain the relevant functions and morphological characteristics that are essential to the system. Using regular usage slices, a higher-precision non-uniform rational B-spline (NURBS) usage rate can be fitted and a surface model with better continuity can be constructed. The experimental results show that the deviation of the NURBS usage rate generated by the boundary division from the original data model can reach test accuracies of 83, 87 and 89%, respectively. It is shown that the method can effectively reduce the modeling error caused by the irregular feature model in the process of modeling the utilization rate of digital information, and that it can ensure the accuracy of the model.
- intelligent computing,
- decision support system,
- healthcare management,
- elderly residents
Citation: Yuqing Lu. A knowledge-driven decision support system for remote medical management[J]. Mathematical Biosciences and Engineering, 2023, 20(2): 2732-2749. doi: 10.3934/mbe.2023128

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Abstract

Residential medical digital technology is an emerging discipline combining computer network technology and medical research. Based on the idea of knowledge discovery, this study was designed to construct a decision support system for remote medical management, analyze the need for utilization rate calculations and obtain relevant modeling elements for system design. Specifically, the model constructs a design method for a decision support system for the healthcare management of elderly residents through the use of a utilization rate modeling method based on digital information extraction. In the simulation process, the utilization rate modeling and system design intent analysis are combined to obtain the relevant functions and morphological characteristics that are essential to the system. Using regular usage slices, a higher-precision non-uniform rational B-spline (NURBS) usage rate can be fitted and a surface model with better continuity can be constructed. The experimental results show that the deviation of the NURBS usage rate generated by the boundary division from the original data model can reach test accuracies of 83, 87 and 89%, respectively. It is shown that the method can effectively reduce the modeling error caused by the irregular feature model in the process of modeling the utilization rate of digital information, and that it can ensure the accuracy of the model.

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