A novel multi-echo MRI technique for prostate cancer detection and grading

We propose to develop a novel, clinically relevant MRI based technique for prostate cancer detection. We also propose to develop a novel reporting system that would be more accurate and easier to use by the radiologists. The new technique will be first developed on a research MRI scanner at UBC, and subsequently implemented on the clinical MRI scanner at VGH. The main benefit to the hospital will be a new, improved MRI technique for prostate cancer detection and grading.

Dino Island: Improving Executive Functioning in Very Young Children with Autism Spectrum Disorder

Many children with Autism Spectrum Disorders (ASD) have problems with attention and executive functions (EF). Cognitive interventions have great potential to improve attention/EF and related skills (e.g., academic learning, social function, behaviour etc.), but few such interventions exist with even fewer that can be delivered at home. In light of COVID-19, parent-delivered interventions are crucial for continuity of healthcare for children with ASD. We will evaluate the efficacy of a new attention/EF intervention (Dino Island), as delivered by parents at home to their children with ASD.

The Development and Implementation of a Data Management Strategy for a Community Mental Health Organization

While the use of “big data” in the business world and health sector is well underway, mental health services are slower to use their big data, particularly for research and decision-making purposes. Researchers have identified a need to explore the use of big data in mental health organizations, such as identifying strategies and tools to optimize data use, and examining the role of big data in mental health service delivery and policy development.

Development and Validation of a Needle Decompression Simulator to Support the Acquisition and Maintenance of Advanced Care Paramedics Skills

Paramedics perform a range of services in pre-hospital patient care, often being the first responders for the most critically ill patients. As such, it is crucial for them to learn and retain life-saving clinical procedures throughout their career. Simulation has been designed to provide a way to paramedic training. This project focuses on the development of a 3D printed simulator for training and re-training of the needle decompression procedure, a life saving yet rarely performed procedure.

Dynamic multi-type multi-priority emergency surgery scheduling with accurate service duration estimation

The process of setting surgical schedules in a modern hospital operating room suite is complicated. Scheduling surgery involves coordinating two separate but inter-related service distribution channels, namely, elective surgery operations and emergency surgery operations. Elective surgical cases are selected from a broad range of diagnostic categories and are scheduled in advance into surgical time that usually runs during regular business hours.

Assessing student (dis)engagement: Interrogating how access and equity factor into the university experience

Disengagement is not a “steady state” rather it is better conceptualized on a continuum with engagement in some areas as well as disengagement in others (Christenson and Thurlow 2004). The proposed research will explore how issues of access and equity factor into student engagement within the university setting. In particular, this research explicitly examines “push” and “pull” factors for engagement by drawing on several data sources to assess factors affecting retention rates and the experiences of students who leave post-secondary education.

Development of a Quantitative and Inexpensive Opioid Detector for Clinical Use

The opioid epidemic is a serious health crisis and opioid treatment strategies are at the forefront of efforts to tackle this crisis. Replacement therapy is the current approach taken using medications such as methadone. To be more effective, the dosage needs to be tailored to individual tolerance which requires a point-of-care type analytical measurement of the patient's existing opioid level.

Identification of Physiologic Biomarkers in Patients with ObstructiveSleep Apnea (OSA): A Step Towards a Precision Care Approach

Obstructive sleep apnea (OSA) is a common disease characterized by recurrent collapse of the airway during sleep leading to sleep fragmentation and daytime sleepiness. OSA is usually diagnosed based on an overnight sleep study (polysomnogram) which collects detailed physiologic information over the night. OSA patients are also at increased risk of cardiovascular disease such as heart attacks and strokes.

Temporal soft clustering for profiling and predictive analytics in elderly care homes

Nxtgen Care provides monitoring services for elderly care homes across North America. Their product provides detailed analysis in visual formats to understand the resident’s requirements and directing care in that direction. To meet this goal, voluminous data is collected from the various activities of the residents. Through this project, this data is processed and directed in a way to optimize resources for effective scheduling in a timely manner. This is done with the help of advanced Machine Learning (ML) and Artificial Intelligence (AI) techniques.

Assessment of local air filtration in hospital wards to prevent spread of SARS-CoV2

A major mechanism for the spread of COVID 19 is inhalation of aerosols and droplets produced by an infected person. Localized filtration systems (essentially an air purifier with appropriate inlet and outlet ducting) could provide an important layer of protection in the event that other layers of protection (ie, mask wearing) are compromised. Delta Hospital is developing local air filtration systems that would extract the majority of particles produced by a patient (with or without a mask).

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