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A Deep Learning based Solution (Covi-DeteCT) Amidst COVID-19.

Kavita Pandey1

  • 1Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, India.

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|September 29, 2022
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Summary
This summary is machine-generated.

This study developed an AI-powered mobile app for rapid COVID-19 detection using CT scans. The ResNet101V2 with Feature Pyramid Network model achieved 98.19% accuracy, aiding healthcare professionals and reducing diagnostic errors.

Keywords:
COVID-19CT scanPandemicsResNetdeep learningfeature pyramid network

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Deep Learning

Background:

  • The COVID-19 pandemic strained medical resources, leading to potential diagnostic errors and a shortage of test kits.
  • Rapid and accurate COVID-19 detection remains a significant challenge globally.
  • Existing AI methodologies for COVID-19 detection have not been widely implemented in functional applications.

Purpose of the Study:

  • To develop an accessible platform for COVID-19 identification, contributing to healthcare digitization.
  • To create a system that fuses deep learning with medical imaging for swift and precise COVID-19 diagnosis.
  • To reduce healthcare workers' workload and minimize false detection rates.

Main Methods:

  • Application of deep learning models, including Resnet50V2 and Resnet101V2, for classifying lung CT scan images.
  • Utilizing an adjusted ResNet101V2 model integrated with a Feature Pyramid Network (FPN).
  • Training and evaluating models on a SARS-CoV-2 dataset using metrics like precision, recall, and F1-score.

Main Results:

  • Resnet50V2 achieved 96.79% accuracy; Resnet101V2 achieved 97.79% accuracy.
  • ResNet101V2 with FPN demonstrated superior performance, reaching an accuracy of 98.19%.
  • The best-performing model was integrated into a functional application for user CT image analysis.

Conclusions:

  • A mobile application utilizing ResNet101V2 with FPN provides fast and accurate COVID-19 detection from CT scans.
  • The automated system assists healthcare professionals, reducing workload and the likelihood of misdiagnosis.
  • This AI-driven tool enhances diagnostic capabilities for COVID-19 on smart mobile devices.