登革热感染控制的智能监测解决方案:一种以数字双胞胎为灵感的方法
Ankush Manocha1, Munish Bhatia2, Gulshan Kumar3
1National Institute of Technology, Kurukshetra, 136119, Haryana, India; Lovely Professional University, Jalandhar, 144001, Punjab, India.
Computer methods and programs in biomedicine
|October 19, 2024
概括
这项研究引入了一个以数字双胞胎为灵感的智能医疗系统,提高了登革热预测准确度. 创新的混合模型显著减少了预测错误,改善了传染病监测.
科学领域:
- 智能医疗技术 智能医疗技术
- 传染病监测 传染病监测
- 数字生应用程序 数字生应用程序
背景情况:
- 精确的监测和预测对于减轻传染病影响至关重要.
- 登革热的扩散需要先进的医疗保健技术解决方案.
- 物联网 (IoT) 技术为创新的医疗保健提供了潜力.
研究的目的:
- 为智能医疗保健引入一个以数字双胞胎为灵感的监控架构.
- 提高传染病监测和预测的准确性,特别是登革热.
- 为了利用物联网技术为先进的医疗保健解决方案.
主要方法:
- 开发了一个以数字双胞胎为灵感的系统,用于监测和预测登革热感染易感性.
- 雇佣的k-means集群和人工神经网络用于预测.
- 整合了基于相似性的混合建模方案,并进行了数据驱动的错误校正.
主要成果:
- 该系统在时间延迟,分类准确度 (92.86%),灵敏度 (92.43%),特异性 (91.52%),F测量 (90.86%) 方面表现最佳.
- 通过混合建模实现了预测错误的显著减少48%.
- 在健康监测场景和预测中得到验证的有效性.
结论:
- 数字双胞胎系统帮助医疗保健提供者评估登革热病毒的脆弱性.
- 降低了登革热感染对健康造成严重后果的可能性.
- 混合建模和物联网集成增强智能健康监测和预测准确度.
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