Optimization strategies for public health education based on Issa and information system technology
Bibliographic Data
| ID | 22069112 |
|---|---|
| Authors | Zhanyu Ye (King's College London), Yifei Li (0000-0001-5156-0161, Columbia University, corresponding author), Yan Zhang (0000-0001-8460-2671, University of Cambridge) |
| Year | 2025 |
| Volume | 13 |
| Pages | 1523876-1523876 |
| Publication date | 2025-05-08 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2025.1523876 |
| PMID | 40406083 |
| OpenAlex | W4410185980 |
| Language | EN |
| References cited | 34 |
Introduction: Against the backdrop of rapid development of information technology, public health education is facing challenges such as uneven resource allocation and lagging content. Methods: To propose an optimization strategy that can effectively improve the level of public health education, this study improves the sparrow search algorithm by introducing the theory of best point sets to optimize the allocation of public health education resources. Combined with information system technology, a public health education information platform is proposed to optimize public health education. Results: The experiment findings denoted that the improved sparrow search algorithm had a significantly better average fitness value than other compared algorithms after 500 iterations, with an accuracy of 92.4% and an area under the PR curve of 0.84. In practical application, the optimization model for public health education resources increased the balance of resource allocation to 0.89, improved educational effectiveness by 25.5%, and increased user satisfaction by 31.4%. At the same time, the constructed public health education information platform showed excellent performance in terms of CPU usage and time consumption, significantly improving education coverage and content update frequency. Discussion: The above findings indicate that the optimization strategy raised in the study provides scientific basis and practical guidance for the optimization of public health education, which helps to raise the effectiveness and quality of public health education
Data science · Economic growth · Economics · Health care · Health information technology · Information system · Knowledge management · Political science · Public health · Advanced Technologies in Various Fields · Computer Science · Educational Technology and Pedagogy · Ideological and Political Education · Medicine · Nursing
| Citation velocity | historical |
|---|---|
| Highly cited | No |