Covid-19's Rapid diagnosis Open platform based on X-Ray Imaging and Deep Learning

Area of Science:

• Medical Imaging
• Artificial Intelligence
• Epidemiology

Background:

• The Coronavirus epidemic (COVID-19) emerged in late 2019, causing global health system strain.
• Diagnostic testing faced significant pressure due to the rapid spread and high case numbers.
• Rapid screening methods are crucial, especially for resource-limited settings.

Purpose of the Study:

• To develop a rapid screening tool for Coronavirus using X-ray images.
• To leverage Artificial Intelligence (AI) for faster and more accessible diagnosis.
• To create a smart platform to assist healthcare providers in emerging countries.

Main Methods:

• Development of a collaborative and smart platform.
• Utilized the VGG16 Convolutional Neural Network (CNN) model for image classification and detection.
• Integrated patient data entry and X-ray image analysis.

Main Results:

• The platform enables rapid download and processing of X-ray images.
• The VGG16 model facilitates quick analysis, with tests completed in approximately 5 seconds.
• The system generates a PDF report including patient information and analysis results.

Conclusions:

• AI-powered X-ray analysis offers a viable solution for rapid Coronavirus screening.
• The proposed platform can alleviate the burden on testing laboratories.
• This technology can support healthcare systems, particularly in resource-constrained environments.