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A Blockchain-enabled and AI-Supported COVID-19 Detection Method
2022 4th International Conference on Blockchain Computing and Applications, BCCA 2022
  • Farzaneh Bannazadeh, University of Ottawa
  • Malini Manohar, University of Ottawa
  • Rakshit Mitra, University of Ottawa
  • Ismaeel Al Ridhawi, Kuwait College of Science & Technology
  • Ali Abbas, University of Ottawa
  • Mohsen Guizani, Mohamed Bin Zayed University of Artificial Intelligence
Document Type
Conference Proceeding
Abstract
Given that COVID-19 symptoms might be similar to other viral infectious diseases, it becomes difficult to accurately diagnose for COVID-19 without traditional testing strategies like polymerase chain reaction (PCR) testing. As the quarantine and testing requirements have been lifted from most countries, easier and innovative testing strategies are being adopted to maintain high awareness levels in regards to the spread of the disease for both authorities and the public. This paper presents a COVID-19 detection strategy that uses Machine Learning (ML) models to accurately diagnose for the disease in patients. The Artificial Intelligence (AI)-enabled solution not only serves the purpose of detecting whether patients are diagnosed with COVID, but also to track their daily symptoms and accurately classify the type of viral disease. Different ML models are trained and tested for accuracy and prediction timings. A decentralized approach is taken for the disease prediction, and hence, blockchain is adapted within the solution to ensure the authenticity of the user data. The solution has been implemented to allow users to receive real-time disease diagnosis using a web-based interface.
DOI
10.1109/BCCA55292.2022.9922168
Publication Date
10-31-2022
Keywords
  • Artificial Intelligence,
  • Blockchain,
  • COVID-19,
  • Industry 4.0,
  • Machine Learning
Comments

IR conditions: non-described

Citation Information
F. Bannazadeh, M. Manohar, R. Mitra, I. Al Ridhawi, A. Abbas and M. Guizani, "A Blockchain-enabled and AI-Supported COVID-19 Detection Method," 2022 Fourth International Conference on Blockchain Computing and Applications (BCCA), 2022, pp. 4-10, doi: 10.1109/BCCA55292.2022.9922168.