一个人工智能医疗生态系统框架用于Covid-19检测和预测,使用CronaSona
1Information System Department, Faculty of Computers & Information, Suez University, Suez, Egypt. s.hassan@suezuni.edu.eg.
Medical & biological engineering & computing
|March 13, 2024
概括
克罗纳Sona是一个新的医疗保健生态系统框架和用于COVID-19管理的移动应用程序. 它整合了检测,预测和专家建议,以全面控制疾病并改善患者的治疗结果.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 流行病学 流行病学
背景情况:
- 现有的COVID-19解决方案往往只专注于检测或预测.
- 为了有效的疾病管理,需要采用全面,综合的方法.
- 标准化框架可以加速医疗保健应用程序的开发.
研究的目的:
- 推出CronaSona,这是一个针对COVID-19的新型医疗保健生态系统框架.
- 在整体疾病管理框架的基础上开发一个移动应用程序.
- 为开发特定疾病应用程序标准化组件.
主要方法:
- 开发了一个包括利益相关者,共享组件和四个子系统的框架:管理信息,专家,检测/预测和移动跟踪器.
- 构建了CronaSona移动应用程序来实现和测试框架.
- 利用深度学习技术从胸部X射线图像中检测COVID-19.
主要成果:
- 这是一个CronaSona应用程序. 提供综合COVID-19检测,预测和专家建议.
- 深度学习模型在COVID-19检测中实现了高精度 (97%),F1得分 (97.6%) 和精度 (96.6%).
- 框架和应用程序. 他们的目标是加快诊断,尽量减少病毒传播,并帮助患者管理.
结论:
- 克罗纳索纳框架为管理COVID-19提供了一个整体解决方案.
- 开发的应用程序证明了该框架在诊断和疾病控制方面的有效性.
- 克罗纳索纳有可能改善患者护理,减少传染病的影响.
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