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Silwatech is backed by a team of 1000+ employees, serving clients in over 10+ industries across 9+ locations
Mobile Application For Antigen Testing Viral Load
Mobile Application For Antigen Testing Viral Load
The developed mobile application demonstrates promising results in automating antigen testing for COVID-19. By leveraging computer vision and machine learning technologies, the application offers a reliable and efficient solution for identifying COVID-19 test strips, locating test results, and determining COVID-19 status accurately. This contributes to the broader efforts in combating the COVID-19 pandemic by facilitating widespread testing and early detection of infections.
Key Challenges
- Identifying Test Strips: Ensuring the accurate recognition of COVID-19 test strips from images taken across varied conditions and devices.
- Result Localization: Detecting the specific result areas on diverse test strip formats, accommodating differences in design and layout.
- Accurate Diagnosis: Leveraging advanced techniques to reliably determine whether the test result indicates a positive or negative COVID-19 diagnosis.
Our Solutions
- Mobile Application Development: Designed a cross-platform app with an intuitive interface for capturing and processing antigen test results seamlessly.
- Machine Learning Models: Deployed robust ML models to analyze test strips, ensuring precise detection and result classification.
- Automated Antigen Testing: Integrated automation to minimize manual errors and accelerate the antigen testing workflow.
- Improved Accessibility: Enabled healthcare professionals and individuals to easily access and interpret test results directly from their mobile devices.
Tech Stack
Conclusion
The developed mobile application demonstrates promising results in automating antigen testing for COVID-19. By leveraging computer vision and machine learning technologies, the application offers a reliable and efficient solution for identifying COVID-19 test strips, locating test results, and determining COVID-19 status accurately. This contributes to the broader efforts in combating the COVID-19 pandemic by facilitating widespread testing and early detection of infections.
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