Undergrad students in Professor Ghassan Hamarneh’s Biomedical Computing course were encouraged to research the COVID-19 pandemic for their final class project. As part of the course requirements, students were required to work on a biomedical computing topic, meaning that they were to use real-world biomedical data and perform some processing and analysis to come up with meaningful results. Students were also required to write code for their projects. 

“Despite all the negative aspects of COVID-19 and the challenges it continues to create, observing highly motivated students dedicated to learning, with ambition to make significant contributions, was uplifting,” said professor Hamarneh.  

With the support of teaching assistance Mengliu Zhao, the students researched a variety of topics, from classifying viral and bacterial pneumonia based on chest X-ray data, to different approaches on how to research the COVID-19 pandemic. Below are four videos representing some of the research performed in the class. 

Group 1: Jianhong Chen, Sheldon Fries, Wendy Huang, Shanila Javed, James Young 

Group 1 presents an estimation of the currently infected, susceptible and recovered cases of COVID-19 using a SIR Model. 

Group 5: Wilson Chan, Zully Comas, Liam Koochin, Raj Mahey, Salman Siddiqui 

Group 5 forecasts trends in the COVID-19 pandemic in Canada, United States and Italy using long short-term memory networks, a polynomial regression, an ARIMA model and a support vector regression model to compare the data.

Group 8: Jagrajan Bhullar, Sajjad Shamanian Esfahani, Ayman Faisal, Shivansh Sasan, Oleh Sokolov

Group 8 allows users to compare countries’ case counts while looking at factors such as stock market data, indicators of government policies and more during the COVID-19 pandemic.   

Group 20: Ali Arshad, Nick Chubb, Michael Huang, Sina Khalili, Logan Militzer

Group 20 presents “BioBuddy”, which is meant to help calculate the chances of a person having the COVID-19 disease given their symptoms and external factors.  

These videos show a few ways that computing science research can be used during the COVID-19 pandemic to help predict case counts, display useful data and help people interpret their symptoms. 

Links:  
Hamarneh’s research lab: https://www.medicalimageanalysis.com 
Mengliu Zhao: https://www.linkedin.com/in/mengliu-zhao-11117151/ 
CMPT 340 course outline: https://www.sfu.ca/outlines.html?2020/spring/cmpt/340/d100