Leveraging big data in health care and public health for AI driven talent development in rural areas
IntroductionThis study proposes a novel Transformer-based approach to enhance talent attraction and retention strategies in rural public health systems. Motivated by the persistent shortage of skilled professionals in underserved areas and the limitations of traditional recruitment methods, we lever...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-05-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1524805/full |
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| author | Jing Zhou Li Li Jiahang Su |
| author_facet | Jing Zhou Li Li Jiahang Su |
| author_sort | Jing Zhou |
| collection | DOAJ |
| description | IntroductionThis study proposes a novel Transformer-based approach to enhance talent attraction and retention strategies in rural public health systems. Motivated by the persistent shortage of skilled professionals in underserved areas and the limitations of traditional recruitment methods, we leverage big data analytics and natural language processing to address workforce distribution imbalances.MethodsBy analyzing diverse data sources such as social media, surveys, and job satisfaction reports, the Transformer model identifies complex, context-specific factors influencing candidate preferences, including career advancement opportunities, lifestyle alignment, and community engagement.ResultsOur framework offers a personalized, data-driven mechanism to match healthcare professionals with rural roles effectively. Experimental results demonstrate significant improvements in recruitment precision and retention forecasting.DiscussionThis work contributes a scalable and adaptive solution to rural healthcare workforce challenges, offering valuable insights for policy-makers and public health organizations aiming to revitalize rural health services. |
| format | Article |
| id | doaj-art-b99ea620567540819aeb9c3a0ab4e7d4 |
| institution | OA Journals |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj-art-b99ea620567540819aeb9c3a0ab4e7d42025-08-20T01:54:21ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-05-011310.3389/fpubh.2025.15248051524805Leveraging big data in health care and public health for AI driven talent development in rural areasJing Zhou0Li Li1Jiahang Su2School of Pharmaceutical Business, Zhejiang Pharmaceutical University, Ningbo, Zhejiang, ChinaTaizhou Vocation College of Science & Technology, School of Accounting & Finance, Taizhou, Zhejiang, ChinaHuaqiao University, Xiamen, Fujian Province, ChinaIntroductionThis study proposes a novel Transformer-based approach to enhance talent attraction and retention strategies in rural public health systems. Motivated by the persistent shortage of skilled professionals in underserved areas and the limitations of traditional recruitment methods, we leverage big data analytics and natural language processing to address workforce distribution imbalances.MethodsBy analyzing diverse data sources such as social media, surveys, and job satisfaction reports, the Transformer model identifies complex, context-specific factors influencing candidate preferences, including career advancement opportunities, lifestyle alignment, and community engagement.ResultsOur framework offers a personalized, data-driven mechanism to match healthcare professionals with rural roles effectively. Experimental results demonstrate significant improvements in recruitment precision and retention forecasting.DiscussionThis work contributes a scalable and adaptive solution to rural healthcare workforce challenges, offering valuable insights for policy-makers and public health organizations aiming to revitalize rural health services.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1524805/fullbig data in health carepublic health talent developmentAI in rural health systemshealthcare workforce optimizationhealth policy |
| spellingShingle | Jing Zhou Li Li Jiahang Su Leveraging big data in health care and public health for AI driven talent development in rural areas Frontiers in Public Health big data in health care public health talent development AI in rural health systems healthcare workforce optimization health policy |
| title | Leveraging big data in health care and public health for AI driven talent development in rural areas |
| title_full | Leveraging big data in health care and public health for AI driven talent development in rural areas |
| title_fullStr | Leveraging big data in health care and public health for AI driven talent development in rural areas |
| title_full_unstemmed | Leveraging big data in health care and public health for AI driven talent development in rural areas |
| title_short | Leveraging big data in health care and public health for AI driven talent development in rural areas |
| title_sort | leveraging big data in health care and public health for ai driven talent development in rural areas |
| topic | big data in health care public health talent development AI in rural health systems healthcare workforce optimization health policy |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1524805/full |
| work_keys_str_mv | AT jingzhou leveragingbigdatainhealthcareandpublichealthforaidriventalentdevelopmentinruralareas AT lili leveragingbigdatainhealthcareandpublichealthforaidriventalentdevelopmentinruralareas AT jiahangsu leveragingbigdatainhealthcareandpublichealthforaidriventalentdevelopmentinruralareas |