This sickness-detecting AI may be able to accurately identify COVID-19 symptoms using cough recordings. Researchers at the Massachusetts Institute of Technology (MIT) are currently honing in on an algorithm which is detecting the virus' symptoms with a 98.5% success rate.
In a recently published paper, Brian Subirana, an MIT scientist working on the project explained that “The way you produce sound changes when you have COVID-19, even if you’re asymptomatic.” As stated in the same paper, once perfected, this AI could be used for a multitude of purposes, including “practical use cases could be for daily screening of students, workers and public, as schools, jobs and transport reopen, or for pool testing to quickly alert of outbreaks in groups.”
Image Credit: Markus Winkler/Unsplash
Key Themes Behind This Trend
- AI-based Symptom Detection
- Developing AI algorithms that accurately identify COVID-19 symptoms through cough recordings.
- Sound Analysis Technology
- Advancing sound analysis technology to detect changes in sound production caused by COVID-19 infections.
- Practical Applications of AI
- Exploring practical use cases for AI in daily screening, pool testing, and outbreak alert systems.
Where This Applies
- Healthcare
- Implementing AI-based symptom detection technology in healthcare settings to improve screening and diagnosis.
- Education
- Adopting AI symptom detection tools for daily screening of students and staff in educational institutions.
- Transportation
- Integrating AI algorithms in transport systems to screen passengers for COVID-19 symptoms and prevent outbreaks in public transit.
