KAIST researchers behind the Hi-COVIDNet (KAIST)
Researchers from Korea Advanced Institute of Science and Technology have developed a big data and artificial intelligence-powered software called Hi-COVIDNet to monitor incoming COVID-19 cases from overseas.
KAIST said Wednesday that the Hi-COVIDNet predicts the volume of COVID-19 patients’ influx two weeks in advance, based on big data information of foreign nations’ confirmed patient numbers and deaths, the daily number of flights from those nations to Korea and the number of passengers who have signed up for roaming services to Korea among others.
The researchers behind this system, led by professor Lee Jae-gil and Ph.D. candidate Kim Min-seok from the department of Industrial and Systems Engineering, anticipate the program will keep local authorities one step ahead of the pandemic’s spread.
The more widespread the global pandemic, the more at risk local society becomes, said KAIST.
A prediction technology will enable timely bolstering of quarantine facilities and policies for passengers from high-risk nations.
The scholarly article for this software, titled “Hi-COVIDNet: Deep Learning Approach to Predict Inbound COVID-19 Patients and Case Study in South Korea,” will be presented on Aug. 24 at the Association for Computing Machinery’s Knowledge Discovery in Database 2020’s AI for COVID-19 session.
By Lim Jeong-yeo (firstname.lastname@example.org)