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Adedoyin Ahmed Hussain1,2, Ouns Bouachir3,4, Fadi Al-Turjman2

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Summary
This summary is machine-generated.

Artificial Intelligence (AI) aids healthcare by analyzing COVID-19 data. This survey explores AI techniques, including machine learning, for pandemic management, achieving up to 90% accuracy in medical data analysis.

Keywords:
Big dataartificial intelligencecloud computingdeep learningthe IoT

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare
  • Computational Biology

Background:

  • The COVID-19 pandemic highlighted the critical need for advanced data analysis tools in healthcare.
  • Artificial Intelligence (AI) offers powerful capabilities to process vast amounts of medical data.
  • Existing healthcare systems face challenges in managing and interpreting pandemic-related information.

Purpose of the Study:

  • To survey current Artificial Intelligence applications in clinical settings during the COVID-19 crisis.
  • To highlight the role of Big Data analytics in understanding and combating the virus.
  • To provide an overview of intelligence techniques applicable to medical data during pandemics.

Main Methods:

  • Classification of AI techniques in clinical data analysis, including neural networks, Support Vector Machines (SVM), and edge learning.
  • Overview of Big Data applications for virus analysis.
  • Emphasis on AI-oriented cloud computing for combating viral outbreaks.

Main Results:

  • AI techniques demonstrate significant advancements in medical data analysis, achieving up to 90% accuracy.
  • Identified various intelligence methods applicable to pandemic data.
  • Highlighted the utility of AI-driven cloud computing in managing viral threats.

Conclusions:

  • AI implementation offers substantial advantages in combating COVID-19 and similar viral pandemics.
  • Medical practitioners and researchers can leverage AI to overcome challenges in handling big data.
  • Continued development and application of AI are crucial for future public health crises.