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COVID-19 Detection Mechanism in Vehicles Using a Deep Extreme Machine Learning Approach.

Areej Fatima1, Tariq Shahzad2, Sagheer Abbas3

  • 1Department of Computer Science, Lahore Garrison University, Lahore 54000, Pakistan.

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|January 21, 2023
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Summary
This summary is machine-generated.

A novel vehicle-based system uses deep extreme machine learning to detect COVID-19 symptoms like fever and cough. This automated approach aids early detection, crucial for controlling the pandemic and improving public health outcomes.

Keywords:
COVID-19DELMWHOcoronavirusdiagnosishealthcare

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare
  • Epidemiology

Background:

  • The COVID-19 pandemic necessitates rapid and accurate detection methods to curb viral spread and reduce mortality.
  • Current RT-PCR testing faces challenges including long turnaround times and potential false negatives.
  • Automated systems utilizing medical imaging and machine learning are emerging as alternatives for early disease identification.

Purpose of the Study:

  • To propose a Vehicle-based COVID-19 Detection System for early symptom identification in individuals within vehicles.
  • To leverage deep extreme machine learning and fuzzy modeling for accurate COVID-19 detection.
  • To facilitate timely COVID-19 testing and intervention by enabling mobile screening.

Main Methods:

  • Development of a COVID-19 detection system integrated into vehicles.
  • Application of deep extreme machine learning algorithms for symptom analysis.
  • Utilization of fuzzy modeling to account for the ambiguity of human symptoms.
  • Inclusion of key symptoms such as fever, cough, shortness of breath, and pneumonia as detection parameters.

Main Results:

  • The proposed system demonstrated high accuracy in detecting COVID-19 related symptoms.
  • Achieved an accuracy exceeding 90% in the COVID-19 detection model.
  • The vehicle-based approach offers a practical solution for widespread, timely screening.

Conclusions:

  • The Vehicle-based COVID-19 Detection System provides an effective and automated method for early disease detection.
  • This system can significantly assist governments in managing the pandemic through efficient and timely testing.
  • The integration of deep learning and fuzzy logic enhances the reliability of COVID-19 symptom identification.