A Principled Approach to Developing Machine Learning Models for the Synthesis of Structured Health Data

Under the current pandemic of Covid-19, sharing health record data has tremendous benefits to control the spread of the infection and save lives globally. In medical research and discovery, Electronic medical records (EMRs) play the essential role for medical discovery in two categories, namely 1) cross-sectional study and 2) longitudinal study. Cross-sectional study compares different […]

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BI-Driven Management of Patient Flows in Health Care Organizations

Hospitals in Ontario are operating at congestion levels that translate into long wait times, staff burnout, and inefficiencies. Decisions coping with problems are made based on incomplete data which may be days out of date because the data is collected, processed and delivered manually in an ad hoc manner. Furthermore, these decisions may be optimal […]

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Advancing traceability in informal supply chains through applied AI and ML

PemPem develops tools to ensure product traceability in informal supply chains using AI. These informal supply chains employ over 60% of the working population worldwide. They typically have highly inefficient operations due to very limited access to information and a reliance on opaque word-of-mouth coordination. While PemPem has started solving the problem of collecting data […]

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Distributed Learning over Edge Computing to Support Covid-19 Modelling

The proposed research will allow any device to contribute its computing capabilities to the general distributed computer. Combined, these devices become a super-computer — providing resources for researchers and scientists in their quest for discovery. This research focuses on the finely calibrated aspects of scheduling slices of computing on this computing network. The intern will […]

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An examination of gamification methods to improve user engagement: A case study of a system to manage expertise during the COVID-19 Pandemic

totaliQ has developed an expertise management platform that helps organisations save significant time and money by providing them with maximum visibility into the individual expertise that each employee within the organization has and where that employee is located. safetyiQ is a free, light version of this system that will allow employees, managers and occupational health […]

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New designs for Bayesian adaptive cluster randomized trials for an individualized clinical support tool with capacity to support distance follow up and treatment of depression

Depression is a common and often devastating illness that contributes to suffering for patients and families and is also the number one cause of disability globally. Many patients do not respond to their first trial of treatment, and managing depression according to best practices can be difficult for clinicians. Using the power of machine learning, […]

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An ultra-small vital sign monitoring multi-sensing platform

This collaborative research project between iMD research and prof. Benoit Gosselin aims to design and test an tiny, inexpensive and easy-to-use wearable multi-sensing platform to continuously monitor patients remotely, and help greatly to manage COVID-19. The envisioned platform will use CMOS custom integrated circuits and advanced packaging technology to achieve an extreme level of miniaturization. […]

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Development of a solution to assess the quality and to optimize AI-based video codecs

Current video codecs consider algorithms to analyze video imagery in order to find out which bits can be removed for file size reduction without subjective video frame degradation. Integrating AI with encoding process improves the quality of encoding and decoding. AI permits the software to proactively assess the quality of the encoded video before transmission. […]

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Methods for the Estimation of Traffic Matrices

The accurate knowledge of origin/destination traffic matrices allows network operators to efficiently perform network management operations to maximize network performance (minimize network congestion, average delay, jitter, energy consumption, etc.) and increase network reliability in case of device failures and other exceptional events. However, traffic matrices cannot be directly measured, and network operators, such Videotron, can […]

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Mobile Data Usage & Signal Strength – Manage, Analyze and predict estimated data usage and signal strength to conduct automatic cause analysis using deep neural network and unsupervised learning techniques

Enterprise mobility management enables to collect various metrics from million of devices. This industrial research project focuses on identifying the key performance indicators and formulas to identify and predict coverage issues and identify data usage problems within a device. Using the key performance indicators, the intern will explore all feasible machine learning approaches. Final goal […]

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Personnaliser l’accompagnement de consommateurs dans une plateforme numérique de coaching virtuel

Les Éditions Protégez-Vous souhaitent innover dans la diffusion de leur contenu afin d’accompagner les consommateurs dans leurs choix, en particulier avec une plateforme numérique de coaching virtuel. Une première phase consiste à proposer une plateforme avec le contenu du guide pratique « 100 gestes pour la planète » pour accompagner les consommateurs à faire des […]

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