Principal Investigator: Yuguang Michael Fang
Sponsor: NSF
Start Date: September 1, 2017
End Date: August 31, 2021
Amount: $413,000
Abstract
Although current healthcare systems actively collect medical data from patients in hospitals, numerous personal subjective data is commonly neglected in the analysis of environmental public health due to high-sensitivity of health-related data. As a result, there is a lack of real-time monitoring data, such as symptom reports from high-risk groups and severe environmental pollution, causing notoriously long latency for effective prevention of the spread of epidemic diseases. This project is to address the fundamental challenges on collecting and analyzing multi-scale data from multi-sources for environmental public health in a privacy-preserving manner. The developed technologies empower each individual in a community to proactively contribute real-time data of themselves and surroundings for the betterment of public health without compromising his/her privacy. In addition, this project also serves as a training ground for educating future decision-makers and workforce on privacy-preserving healthcare technologies.
More Information: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1722791&HistoricalAwards=false