数字通信与网络(英文)2024,Vol.10Issue(1) :75-82.DOI:10.1016/j.dcan.2022.09.004

An artificial intelligence diabetes management architecture based on 5G

Ruochen Huang Wei Feng Shan Lu Tao shan Changwei Zhang Yun Liu
数字通信与网络(英文)2024,Vol.10Issue(1) :75-82.DOI:10.1016/j.dcan.2022.09.004

An artificial intelligence diabetes management architecture based on 5G

Ruochen Huang 1Wei Feng 2Shan Lu 3Tao shan 3Changwei Zhang 4Yun Liu5
扫码查看

作者信息

  • 1. Department of Information,The First Affiliated Hospital of Nanjing Medical University,Nanjing,210096,China
  • 2. Department of Medical Informatics,School of Biomedical Engineering and Informatics,Nanjing Medical University,Nanjing,211166,China
  • 3. Department of Outpatient,The First Affiliated Hospital of Nanjing Medical University,Nanjing,210096,China
  • 4. Jiangsu Key Laboratory of Wireless Communications,Nanjing University of Posts and Telecommunications,Nanjing,210003,China
  • 5. Department of Geriatrics,The First Affiliated Hospital of Nanjing Medical University,Nanjing,210096,China;Department of Medical Informatics,School of Biomedical Engineering and Informatics,Nanjing Medical University,Nanjing,211166,China
  • 折叠

Abstract

Along with the development of 5G network and Internet of Things technologies,there has been an explosion in personalized healthcare systems.When the 5G and Artificial Intelligence(AI)is introduced into diabetes man-agement architecture,it can increase the efficiency of existing systems and complications of diabetes can be handled more effectively by taking advantage of 5G.In this article,we propose a 5G-based Artificial Intelligence Diabetes Management architecture(AIDM),which can help physicians and patients to manage both acute com-plications and chronic complications.The AIDM contains five layers:the sensing layer,the transmission layer,the storage layer,the computing layer,and the application layer.We build a test bed for the transmission and application layers.Specifically,we apply a delay-aware RA optimization based on a double-queue model to improve access efficiency in smart hospital wards in the transmission layer.In application layer,we build a prediction model using a deep forest algorithm.Results on real-world data show that our AIDM can enhance the efficiency of diabetes management and improve the screening rate of diabetes as well.

Key words

Diabetes/5G/Artificial intelligence/Deep forest/Smart hospital ward

引用本文复制引用

基金项目

industry prospecting and common key technology key projects of Jiangsu Province Science and Technology Department(BE2020721)

Special guidance funds for service industry of Jiangsu Province Development and Reform Commission(20191089)

big data industry development pilot demonstration project of Ministry of Industry and Information Technology of China(2019243)

big data industry development pilot demonstration project of Ministry of Industry and Information Technology of China(202084)

Industrial and Information Industry Transformation and Upgrading Guiding Fund of Jiangsu Economy and Information Technology (20180419)

Research Project of Jiangsu Province Sciences(2019-2020ZZWKT15)

found of Jiangsu Engineering Research Center of Jiangsu Province Development and Reform Commission(20201460)

found of Jiangsu Digital Future Integration Innovation Center(2018498)

出版年

2024
数字通信与网络(英文)

数字通信与网络(英文)

ISSN:
参考文献量23
段落导航相关论文