Integrating Cyber-Physical System with Federated-Edge Computing for Diabetes Detection and Management-Reference-Cited by-同舟云学术

Integrating Cyber-Physical System with Federated-Edge Computing for Diabetes Detection and Management

Published:2023-10-20 Issue: Volume: Page:16-22
ISSN:
Container-title:Proceedings of the 2023 5th International Conference on Big-data Service and Intelligent Computation
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Author:

Khater Heba M¹^ORCID,Tariq Asadullah¹^ORCID,Sallabi Farag²^ORCID,Serhani Mohamed Adel³^ORCID,Baraka Ezedin¹^ORCID

Affiliation:

1. UAE University, United Arab Emirates

2. College of Information Technology, UAE University, United Arab Emirates

3. University of Sharjah, United Arab Emirates

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3633624.3633627

Reference20 articles.

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2. [2]Oguntibeju, O.O., 2019. Type 2 diabetes mellitus, oxidative stress and inflammation: examining the links. International journal of physiology, pathophysiology and pharmacology, 11(3), p.45.

3. Identifying Heterogeneity of Diabetics Mellitus Based on the Demographical and Clinical Characteristics

4. [4]Kumar P. Chauhan S. and Awasthi L.K. 2023. Artificial intelligence in healthcare: review ethics trust challenges & future research directions. Engineering Applications of Artificial Intelligence 120 p.105894.

5. Machine learning and artificial intelligence based Diabetes Mellitus detection and self-management: A systematic review

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