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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
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Updated: Sep 9, 2025

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
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通过智能技术进行适应性残疾预测和医疗分析

Malak Alamri1,2, Mamoona Humayun3, Khalid Haseeb4

  • 1Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakaka 72311, Saudi Arabia.

Diagnostics (Basel, Switzerland)
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概括

这项研究引入了使用医疗物联网 (IoMT),边缘计算和人工智能进行准确的实时残疾识别的自适应框架. 它增强了数据安全性和个性化医疗干预措施,

关键词:
人工智能疾病诊断边缘计算医疗保健系统可穿戴式传感器

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科学领域:

  • 医疗信息学
  • 生物医学工程
  • 医疗保健中的人工智能

背景情况:

  • 医疗行业5.0使用无线技术通过生物传感器持续监测患者.
  • 现有系统在及时个性化疾病检测方面面临可扩展性和可靠性挑战.
  • 持续监测对于准确的诊断至关重要,尤其是慢性疾病.

研究的目的:

  • 通过IoMT,边缘计算和人工智能提出适应性和安全性的残疾识别框架.
  • 解决及时发现疾病的局限性,并加强个性化医疗保健.
  • 提高医疗数据分析的安全性和可靠性.

主要方法:

  • 整合轻量级边缘计算以快速收集生物传感器的数据.
  • 实施分散的战略,以确保大数据的安全分析和真实数据的访问.
  • 使用联合学习和轻量级加密来保护数据.

主要成果:

  • 在基于边缘的残疾检测中具有高准确性.
  • 提高云服务器的快速响应时间.
  • 通过先进技术确保敏感医疗数据的安全性.

结论:

  • 拟议的框架提供了安全有效的残疾识别解决方案.
  • 利用IoMT,边缘计算和人工智能来克服实时监控的挑战.
  • 提高诊断准确性并确保敏感医疗数据的保护.