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Research Article

A Comprehensive Exploration of Artificial Intelligence Methods for COVID-19 Diagnosis

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  • @ARTICLE{10.4108/eetpht.10.5174,
        author={Balasubramaniam S and Arishma M and Satheesh Kumar K and Rajesh Kumar Dhanaraj},
        title={A Comprehensive Exploration of Artificial Intelligence Methods for COVID-19 Diagnosis},
        journal={EAI Endorsed Transactions on Pervasive Health and Technology},
        volume={10},
        number={1},
        publisher={EAI},
        journal_a={PHAT},
        year={2024},
        month={2},
        keywords={Machine Learning, COVID-19, Disease Diagnosis, Artificial Intelligence},
        doi={10.4108/eetpht.10.5174}
    }
    
  • Balasubramaniam S
    Arishma M
    Satheesh Kumar K
    Rajesh Kumar Dhanaraj
    Year: 2024
    A Comprehensive Exploration of Artificial Intelligence Methods for COVID-19 Diagnosis
    PHAT
    EAI
    DOI: 10.4108/eetpht.10.5174
Balasubramaniam S1,*, Arishma M1, Satheesh Kumar K1, Rajesh Kumar Dhanaraj2
  • 1: University of Kerala
  • 2: Symbiosis International University
*Contact email: baluttn@gmail.com

Abstract

INTRODUCTION: The 2019 COVID-19 pandemic outbreak triggered a previously unseen global health crisis demanding accurate diagnostic solutions. Artificial Intelligence has emerged as a promising technology for COVID-19 diagnosis, offering rapid and reliable analysis of medical data. OBJECTIVES: This research paper presents a comprehensive review of various artificial intelligence methods applied for the diagnosis, aiming to assess their effectiveness in identifying cases, predicting disease progression and differentiating from other respiratory diseases. METHODS: The study covers a wide range of artificial intelligence methods and with application in analysing diverse data sources like chest x-rays, CT scans, clinical records and genomic sequences. The paper also explores the challenges and limitations in implementing AI -based diagnostic tools, including data availability and ethical considerations. CONCLUSION: Leveraging AI’s potential in healthcare can significantly enhance diagnostic efficiency crisis management as the pandemic evolves.

Keywords
Machine Learning, COVID-19, Disease Diagnosis, Artificial Intelligence
Received
2023-11-18
Accepted
2024-02-13
Published
2024-02-21
Publisher
EAI
http://dx.doi.org/10.4108/eetpht.10.5174

Copyright © 2024 Balasubramaniam S et al., licensed to EAI. This is an open access article distributed under the terms of the CC BYNC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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