针对智能医疗保险系统的安全技术驱动架构:实证研究
Fatima Al-Quayed1, Mamoona Humayun2, Sidra Tahir3
1Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakakah 72341, Saudi Arabia.
Healthcare (Basel, Switzerland)
|August 26, 2023
概括
本研究介绍了用于欺诈检测和预防 (SHINFDP) 的智能医疗保险框架. 它有效地在早期发现医疗保健欺诈,提高保险安全性和效率.
科学领域:
- 医疗保险的健康保险是什么
- 欺诈检测 欺诈检测 欺诈检测
- 信息安全信息安全.
背景情况:
- 随着医疗保健成本的上升和健康问题的增加,需要强大的医疗保险解决方案.
- 医疗保险欺诈对个人,企业和政府构成重大财务风险,需要先进的检测机制.
- 敏感电子健康数据的大量传播吸引了欺诈活动,突出了加强安全措施的紧迫性.
研究的目的:
- 为欺诈发现和预防 (SHINFDP) 提出一个智能医疗保险框架.
- 利用区块链,5G,云和机器学习 (ML) 等尖端技术来改善医疗保险流程.
- 通过早期发现欺诈行为,提高医疗保险的安全性和有效性.
主要方法:
- 开发一个智能医疗保险框架,用于欺诈检测和预防 (SHINFDP).
- 区块链,5G,云计算和机器学习 (ML) 技术的整合.
- 通过数学建模,工业焦点小组和案例研究进行评估.
主要成果:
- 医疗保健欺诈 SHINFDP框架在早期发现医疗保健欺诈方面表现出有效性.
- 数学建模和焦点小组评估表明框架的适应性和易于理解.
- 一个案例研究验证了SHINFDP在现实环境中的实际适用性和影响.
结论:
- 拟议的SHINFDP框架显著提高了医疗保险的安全性和有效性.
- 通过综合技术方法,可以提前发现医疗欺诈行为.
- SHINFDP为医疗保险行业提供了一个可扩展和可理解的解决方案.
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