智能能源意识热交换机优化与深度学习模型,用于物联网启用智能医疗保健
Mahmoud Ragab1,2,3, Sami Saeed Binyamin4
1Information Technology Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Journal of healthcare engineering
|July 24, 2023
概括
本研究介绍了一个智能能源意识的热交换优化与深度学习 (IEA-TEODL) 模型,用于物联网 (IoT) 支持的智能医疗保健. 国际能源署-TEODL模型增强了疾病诊断,并优化了物联网设备集群,以改善医疗保健服务.
科学领域:
- 计算机科学 计算机科学
- 生物医学工程 生物医学工程
- 人工智能的人工智能
背景情况:
- 物联网 (IoT) 和先进传感器的整合正在通过连接设备,患者和专业人员来彻底改变医疗保健.
- 智能医疗保健系统提高了患者安全,可访问性和运营效率,同时降低了成本.
研究的目的:
- 开发一个智能能源意识的热交换优化与深度学习 (IEA-TEODL) 模型,以实现物联网智能医疗.
- 为了有效地集成物联网设备,并在智能医疗保健部门中增强疾病诊断.
主要方法:
- 拟议的IEA-TEODL模型使用了基于能量意识的混乱热交换优化聚类 (EACTEO-C) 方案来分组设备.
- 疾病分类是使用预处理,K-medoid集群来删除异常值,多头注意力双向长期短期记忆 (MHA-BLSTM) 和加权Salp Swarm算法 (WSSA) 进行的.
主要成果:
- 国际能源署-TEODL方法通过删除异常值和基于WSSA的超参数优化,证明了增强的分类结果.
- 在基准数据集上进行了广泛的模拟,证实了IEA-TEODL技术在各种评估指标上与现有方法相比具有更高的性能.
结论:
- 开发的IEA-TEODL模型为支持物联网的智能医疗保健系统提供了重大进步.
- 拟议的技术有效优化物联网设备集群,提高疾病诊断的准确性,为更高效和更具成本效益的医疗保健解决方案铺平道路.
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