Employing Data Mining and Visualization Strategies for the Analysis of Well-being Indicators

In this project, an online, interactive map visualization tool will be built to illustrate trends of community well-being indicators across Nova Scotia using the 2019 Quality of Life survey as the primary source of information. The goal is to empower residents and decision-makers to understand unique well-being patterns and socio-economic trends in communities, providing an invaluable resource for planners, researchers, and policymakers, and even allow Nova Scotians to make informed decisions on where to live.

Telehealth group interventions for addictions in a community mental health setting during the COVID-19 pandemic

Health services delivered over the internet, often referred to as telehealth services, are becoming an increasingly important way of providing healthcare. This has been highlighted by the COVID-19 pandemic and the necessary shift to online service delivery for many organizations that followed. Although there is some evidence that telehealth delivered mental health services are as effective as in person services, this evidence is limited to certain mental health issues, populations, and types of interventions.

Evaluation of Resiliency in Community Youth Empowerment Programs - Year two

Youths experience increased vulnerability to mental health challenges associated with their development and living contexts. Effective mental health promotion must consider the multidimensional determinants of resilience. To address these needs, Dr. Jenny Liu (Elevate applicant) has developed and validated an innovative model, Multi-System Model of Resilience (MSMR), which measures resilience capacities and needs at the individual, community, and structural levels. In collaboration with Hong Fook Mental Health Association (HFMHA) and with mentorship from Dr.

Exploration of neuronal hyperexcitability in human spinal cord tissue models of pathological pain

Chronic pain is a devastating disease that lacks safe and effective treatments. Development of new pain therapeutics depends on understanding the spinal circuitry underlying chronic pain, but most previous studies focus on this circuitry in male rodents. Our previous work has developed tools for studying the spinal cord pain system using human organ donor tissue to address the translation gap in pain research. Here, we will expand on our human tissue models to study the spinal cord circuitry that underlies chronic pain using cutting-edge technology.

Characterization of adverse events, health-care costs and real-world survival outcomes with the introduction of ibrutinib for chronic lymphocytic leukemia/small lymphocytic lymphoma patients in British Columbia

Ibrutinib has proven to be very effective in newly diagnosed and relapsed chronic lymphocytic leukemia (CLL) patients. However, it can cause certain side effects that can lead to early discontinuation of treatment and worse outcomes for patients. The goal of this study is to determine the frequency of side effects in the “real-world” associated with ibrutinib compared to standard therapy using provincial administrative data.

Enhancing Blockchain Security and Performance for Health Records

To prevent and/or recover from pandemics Molecular You plans to use their MyPDx solution that runs over Hyperledger Indy, a self-sovereign identity and health data platform to provide access to researchers, machine learning and analytics applications to data. However, Hyperledger Indy compatible blockchains, such as Sovrin, suffer from scalability limitations. This means when the size of a network grows, message complexity grows exponentially along with memory and processing time, resulting in significant performance degradation.

Evaluation of the mechanical properties of the bone-implant interface in dental implants

Skin-penetrating bone-anchored implants are used in a variety of applications to provide tremendous functional benefits to patients. Globally, the dental implant industry has been valued at 5.08 billion USD where implants are used for replacing single teeth, for larger prostheses, and for full dental arches. The success of these implants relies on a structural integration between the implant and the living bone. Evaluation of the integrity of the bone-implant interface is important to prescribe loading, to identify the risk of failure, and to monitor the long-term health of the implant.

Validating Artificial Intelligence Algorithms for Breast Cancer Detection

While mammograms remain the best available technology for early detection of breast cancer, there are a high number of false positive mammograms and biopsies, leading to increased costs to the medical system on follow-up procedures and increased patient anxiety. This project evaluates the performance of artificial intelligence (AI) systems for breast cancer detection using about 100,000 digital mammograms from the BC Cancer Breast Screening Program.

Development of a market prototype of a smart toothbrush for individuals with advance dementia

Dementia in general and Alzheimer Disease in particular are among the most challenging health conditions in our century. Experiencing cognitive decline, resulting in relying on others for daily living activities and impairment in basic mental tasks are the main symptoms. There are yet no proven treatments to slow or prevent Alzheimer's Disease or dementia progression; thus, they eventually need full-time care. To help patients to stay at their own home longer and ease the caregiver burden, Smart Assistive Technology (SAT) products may be greatly beneficial.

DARSA (Deep-learning Assisted Radiological Software Application):Innovative Machine Learning approaches for Detecting Pathology inImages

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.