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Updated: Sep 22, 2025

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Deep Learning-Based COVID-19 Detection Using CT and X-Ray Images: Current Analytics and Comparisons.

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This study introduces deep learning models for detecting COVID-19 using CT and X-ray scans. It also analyzes global COVID-19 spread data to aid researchers and practitioners.

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Epidemiology

Background:

  • The COVID-19 pandemic, caused by SARS-CoV-2, has led to a significant global health crisis with millions of infections and deaths.
  • Rapid detection and understanding of disease spread are crucial for effective pandemic management.

Purpose of the Study:

  • To present deep learning-based methods for COVID-19 detection using medical imaging (CT and X-ray).
  • To perform data analytics on the global spread of COVID-19.
  • To systematize current research and provide tools for researchers and practitioners.

Main Methods:

  • Application of deep learning algorithms for analyzing chest CT and X-ray images to identify COVID-19.
  • Utilizing data analytics techniques to study the worldwide transmission patterns of the virus.

Main Results:

  • Demonstrated the efficacy of deep learning in detecting COVID-19 from medical images.
  • Provided insights into the global spread dynamics of COVID-19 through data analysis.

Conclusions:

  • Deep learning methodologies offer a promising approach for rapid COVID-19 diagnosis.
  • Data analytics on disease spread is essential for informed public health strategies during pandemics.