Using Machine Learning to Predict 30-Day Risk of Hospitalization, Emergency Visit or Death Among Albertans Who Received Opioid Prescriptions

When utilizing and implementing ML for prediction using administrative health data, two key issues are ML algorithm evaluation and generalizability21. Current approaches evaluate model performance by quantifying how closely the prediction made by the model matches known health outcomes. Evaluation metrics include sensitivity, specificity, and positive predictive value, as well as measures such as the […]

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Efficient Learning Methods for Multimodal Understanding

The main focus of this research is to develop representation learning architectures and algorithms that can help perform various multimodal understanding tasks, and at the same time reduce the need for human supervision in the form of costly annotations. To achieve this goal, a learning system must be able to: (1) learn new tasks or […]

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Exploring perceptions on the QUIT smartcase to guide continued development of this digitally enhanced technology for reducing and quitting dependence on e-cigarettes.

There is growing evidence that e-cigarettes, also known as vaping, have led to an upsurge health risk to young people in Canada, including long-term harm to brain development and respiratory health. Due to such adverse effects, more and more young people indicate a desire to quit. However, such desires often become unsuccessful due to the […]

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Advancing Tele-Rheumatology Platform

This project is the extension project of the previous Tele-rheumatology project. In the previous project, we have designed and developed three components: hardware platform, which is the capturing device for rheumatoid arthritis patience movements by using both 2D and 3D cameras; the capture system, which is used by general practitioners to control the hardware platform; […]

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LIDAR urban scene infrastructure asset feature extraction

Canadian Communities are facing a tidal wave of physical infrastructure debt as their physical assets deteriorate due to age. This project aims to use urban LiDAR data (“streetscapes”) and computer vision to identify key physical assets such as (signs, curbs, centerline roads, streetlights, and other features) by there location (latitude / longitude) and key physical […]

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Design Automation and Optimization Using Artificial Intelligence

The goal of our proposal is to develop three automated processes in the field of construction using artificial intelligence. The first process is to develop a method that can convert two-dimensional drawings into three-dimensional models that can be further manipulated on a computer. The second process is to optimize the cutting of raw materials– such […]

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Développement d’un algorithme de reconnaissance d’images de papillons tropicaux

Le nombre d’espèces qui nous entourent est si important qu’il peut être ardu, même pour les spécialistes, de toutes les identifier. Cela est particulièrement vrai pour les insectes. De plus, avec l’avènement des technologies mobiles de l’information, la quantité et la qualité des images disponibles n’a jamais été aussi importante. Grâce aux appareils photos numérique […]

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Anomaly detection and action recognition for mobile cameras

In this project we want to develop a few AI algorithms for the security and public health monitoring applications that can be implemented on a mobile camera. This camera can be either mounted on the autonomous mobile robot or on the wearable devices that security guards are equipped with. This project is aiming to solve […]

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Unmanned Aerial Vehicle Swarm Collaboration for Weed Control in Field Crops

Precision.ai is building solutions to minimize chemical consumption while maintaining weed control through Intelligent UAV based application. Precision.ai has working survey drones that can fly a field, capture images and use AI to map weeds to be sprayed later. Precision.ai also has “See & spray” drones that can fly a field, identify weeds and spray […]

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Development and Application of Marine Mammal Density Estimation Methods for Directional and Omnidirectional Hydrophones

Estimates of the population density of marine mammals in an area and the change in population over space and time are critical inputs for managing the interactions of human activity and mammal populations. Visual surveys from boats, shore stations, and aircraft have served as the basis for most population estimates currently used by managers. However, […]

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Multi-institute domain adaptation by adversarial constrained medical time series representation learning

Hospitals strive to perform cutting edge medical treatment, treat all patients fairly, and reduce operating costs, while also enabling caregivers to spend more time interacting with patients. Artificial intelligence and machine learning promise these things. However, medical data provides unique challenges for machine learning. Currently, if a hospital wants to include an algorithm for automated […]

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