Preparation and Challenges in Developing a Big Data Analysis Framework in Occupational Medicine in Indonesia.

Q3 Medicine Journal of UOEH Pub Date : 2024-01-01 DOI:10.7888/juoeh.46.113
Aria Kekalih, Nuri Purwito Adi, Dewi Sumaryani Soemarko
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Abstract

This mini review explores the transformative potential of big data analysis and artificial intelligence (AI) in reforming occupational medicine in Indonesia. Emphasizing the preconditions, case studies, and benefits, it underscores the role of big data in enhancing worker well-being. The review highlights the importance of informative health big data, especially in high-risk industries, with examples of case studies of AI implementation in occupational medicine during the COVID-19 pandemic and other relevant scenarios. While acknowledging the challenges of AI implementation, the essay identifies the role of academic and professional organizations as pioneers in big data utilization. Six potential benefits that are identified, including improved patient care and efficient resource allocation, demonstrate the transformative impact of big data analysis. The proposed pathway of preparation underscores the need for awareness, skill enhancement, and collaboration, addressing challenges in data management and stakeholder engagement. The conclusion emphasizes continuous assessment, feasibility studies, and commitment as essential steps in advancing occupational medicine through big data analysis.

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在印度尼西亚开发职业医学大数据分析框架的准备工作和挑战。
这篇微型综述探讨了大数据分析和人工智能(AI)在印度尼西亚职业医学改革中的变革潜力。它强调了前提条件、案例研究和益处,突出了大数据在提高工人福利方面的作用。综述强调了信息化健康大数据的重要性,尤其是在高风险行业,并举例说明了在 COVID-19 大流行和其他相关情况下在职业医学中实施人工智能的案例研究。在承认人工智能实施面临挑战的同时,文章指出了学术和专业组织作为大数据利用先驱的作用。文章指出了六种潜在的益处,包括改善患者护理和提高资源分配效率,这表明了大数据分析的变革性影响。建议的准备途径强调了提高认识、提高技能和开展合作的必要性,解决了数据管理和利益相关者参与方面的挑战。结论强调,持续评估、可行性研究和承诺是通过大数据分析推动职业医学发展的必要步骤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of UOEH
Journal of UOEH Medicine-Medicine (all)
CiteScore
1.30
自引率
0.00%
发文量
35
期刊介绍: Published quarterly: 1 annual volume consisted of 4 numbers. Issued on the 1st of March, June, September and December, respectively.
期刊最新文献
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