The FluSense model was developed by researchers at University of Massachusetts Amherst and tested in campus clinic waiting rooms. The AI platform was able to analyze coughing sounds and crowd size collected by the handheld device in real-time, then use that data to accurately predict daily illness rates in each clinic, according to the study.
Ultimately, once the model has been tested in other geographic locations and different areas, such as hospitals and larger public spaces, the researchers suggested that it may allow public and global health experts to predict the spread of the seasonal flu and pandemics such as COVID-19 more accurately, allowing them to be more proactive in establishing vaccine campaigns, enacting travel restrictions and allocating medical supplies, according to a March 19 news release.
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