在医疗管理中结合模拟模型和机器学习:策略和应用
Alfonso Maria Ponsiglione1, Paolo Zaffino2, Carlo Ricciardi1
1Department of Electrical Engineering and Information Technology, University of Naples 'Federico II', Naples 80125, Italy.
Progress in biomedical engineering (Bristol, England)
|December 10, 2024
概括
结合模拟模型和人工智能 (AI),提高了医疗保健管理. 本系统性审查强调了机器学习与基于代理或离散事件模拟作为改善卫生服务的关键策略.
科学领域:
- 生物医学工程 生物医学工程
- 医疗保健服务研究 医疗服务研究
- 计算健康 计算健康
背景情况:
- 模拟模型和人工智能 (AI) 是医疗保健和生物医学工程中的重要工具.
- 这两种方法都在分析和优化医疗保健流程方面取得了成功.
- 整合模拟和人工智能为提高医疗服务质量提供了一个强有力的战略.
研究的目的:
- 系统地审查结合模拟模型和人工智能的研究,以应对医疗保健管理方面的挑战.
- 确定和讨论整合模拟和AI的主要策略.
- 概述主要的医疗保健应用场景,工具和算法.
主要方法:
- 进行了系统的文献审查.
- 选的数据库包括Scopus,科学网络和PubMed.
- 独立审查员选了应用混合模拟和AI方法的研究.
主要成果:
- 机器学习成为与模拟模型相结合的最普遍的AI策略.
- 基于代理和离散事件系统是主要的模拟方法.
- 审查发现了研究的稀缺性和异质性,表明缺乏标准化的框架.
结论:
- 混合机器学习模拟方法对医疗保健管理具有重大潜力.
- 为了有效地实施这些混合模型,需要一个标准化的框架.
- 未来的研究应该专注于开发用于临床翻译的智能化模型.
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