no code implementations • 14 Sep 2021 • Audrey G. Chung, Maya Pavlova, Hayden Gunraj, Naomi Terhljan, Alexander MacLean, Hossein Aboutalebi, Siddharth Surana, Andy Zhao, Saad Abbasi, Alexander Wong
As the COVID-19 pandemic continues to devastate globally, one promising field of research is machine learning-driven computer vision to streamline various parts of the COVID-19 clinical workflow.
1 code implementation • 5 Aug 2021 • Alexander MacLean, Saad Abbasi, Ashkan Ebadi, Andy Zhao, Maya Pavlova, Hayden Gunraj, Pengcheng Xi, Sonny Kohli, Alexander Wong
The Coronavirus Disease 2019 (COVID-19) pandemic has impacted many aspects of life globally, and a critical factor in mitigating its effects is screening individuals for infections, thereby allowing for both proper treatment for those individuals as well as action to be taken to prevent further spread of the virus.
2 code implementations • 18 Mar 2021 • Ashkan Ebadi, Pengcheng Xi, Alexander MacLean, Stéphane Tremblay, Sonny Kohli, Alexander Wong
The COVID-19 pandemic continues to have a devastating effect on the health and well-being of the global population.
no code implementations • 24 Oct 2019 • Kaylen J. Pfisterer, Robert Amelard, Audrey G. Chung, Braeden Syrnyk, Alexander MacLean, Heather H Keller, Alexander Wong
We propose a novel deep convolutional encoder-decoder food network with depth-refinement (EDFN-D) using an RGB-D camera for quantifying a plate's remaining food volume relative to reference portions in whole and modified texture foods.