Rheumatoid arthritis (RA) is an autoimmune disease often characterized by the inflammation of the synovium and effusion of joints. RA is a chronic condition and may affect quality of life. Detection and characterization of the synovium and effusion in joints is most often assessed by a trained sonographer or radiologist. Recently ultrasound has been brought into the clinic and used by other trained healthcare professionals such as clinicians and physiotherapists.
The effectiveness of cancer drugs depends on several factors which are governed by the genetic and ‘epigenetic’ code of cancer cells. The epigenetic code comprises those heritable modifications that bookmark DNA and DNA-associated proteins to guide the expression of genetic attributes without changing the DNA sequence. This epigenetic code is written, read, and erased by a group of proteins known as epigenetic regulators.
Fungal pathogens cause life-threatening invasive infections in humans. Despite all available treatments, mortality rates remain unacceptably high, on par with deaths caused by infectious diseases such as tuberculosis and malaria. Alarmingly, the emergence of drug-resistant fungi is reducing already limited treatment options. To address needs for new antifungal medications, Amplyx Pharmaceuticals has developed fosmanogepix, a drug which attacks fungi by blocking their ability to build their cell wall, a structure needed to survive and invade humans.
Many aspects of healthcare are time consuming and error prone. Recently there has been great progress in using artificial intelligence to solve a number of problems. One of the best examples of this is image labelling using a type of neural network approach called deep learning. Recent research has shown that deep learning approaches can outperform expert human radiologists when diagnosing disease in chest x-rays, in some situations. In this project we use a large set of chest x-rays as a test bed and develop a new method for software based radiological diagnosis using deep learning models.
This program will cement Canada’s leadership in global Very Long Baseline Interferometry (VLBI), a key technology in radio astronomy and geodesy. In partnership with Thoth Technology Inc., our team of leading radio astronomers will (i) develop new capabilities to compress, transport, and process large amounts of data between geographically distinct locations to enable real-time VLBI, and (ii) use this capability to make precise astrometric measurements of Fast Radio Bursts (FRBs) and pulsars, and through their scintillation properties, study their local environments.
Emerging therapeutic agents that function through the brain’s neurotransmitter systems have recently shown robust benefits in a number of otherwise challenging to treat neurological conditions including depression and post-traumatic stress disorder. The long-term changes that these agents induce within neural tissue is still however unclear. This MITSCS program aims to to use expertise in tissue bioengineering models to explore the molecular changes that modulation of these pathways induces in neuronal cells.
The closure of schools across Canada during the COVID-19 pandemic has revealed significant gaps in educational provision. In addition, K-12 teachers have had difficulty finding learning resources related to the programs they are responsible for teaching. When students fall behind in school, they develop a learning gap with their peers. Learning gaps are relatively common and invariably require, at some point, a strategy to help the student catch up.
The intern will participate in NEUROCOVID19, a project studying how the COVID-19 virus can potentially infect and damage the brain. The intern will develop methods for analyzing magnetic resonance imaging (MRI) of the brain and of the lung, as acquired from people who are no longer infected, and people who were never infected. The intern will also develop new MRI methods for enhanced imaging of brain areas that are damaged by COVID-19 infection.
A geospatial query is a question where the concept of location is necessary for formulating the answer. Furthermore, we are not simply interested in spatial relationships, but also with the ways in which people can possibly move through space given the goals that they want to achieve. We therefore want to predict the behaviour of people moving through urban environments based on observations about their purchases. In this project, we will explore how can models of commonsense knowledge can be used for automated reasoning to answer geospatial queries and to infer consumer behaviour.
COVID-19 impacts on travel are unprecedented, affecting virus-spread, transportation services delivery, and how people will eventually safely participate in economic, educational and social activities. These impacts vary substantially across neighbourhoods, often worsening existing inequities in Canadian cities. This project will accelerate research for deriving insights about COVID-19 from TELUS network location data. Specifically, it will develop new methods to use cellphone traces to measure, model, and evaluate our response to COVID-19’s disruption of daily activity/travel participation.