Real-time food analysis using deep learning for Diabetes Self -Monitoring

Our proposed research is to create an algorithm capable of pre-evaluating diabetes patients’ meals before they consume them with the snap of a picture. We are attempting to accomplish this goal by employing AI, machine learning as well as computer vision for real-time analysis. Our goal is to analyse a users meal to return an accurate carb count and offer portion size adjustments to reduce their blood sugar fluctuations.

Is Obstructive Sleep Apnea a Novel Risk Factor for Cancer?

Obstructive Sleep Apnea (OSA) is an important disease characterized by recurrent blockages of the upper airway during sleep leading to breathing cessations (up to 100 times per hour); OSA is common and is widely under-diagnosed. OSA might cause cancer or lead to cancer progression, potentially mediated through low oxygen levels; however, evidence for this association is limited. This research study will use rigorous methods to determine if there is a potential link between OSA and cancer; specifically, we will link our large database of approximately 1800 patients with suspected OSA.

Targeting granzyme B with a novel inhibitor for the treatment of radiodermatitis

Radiodermatitis is a group of skin reactions that occur as a result of radiation therapy. It is a significant health challenge as approximately 70% of all cancer patients receive radiation therapy and approximately 95% of them experience radiodermatitis. Patients with radiodermatitis experience redness, itchiness, pain, scaling, and weeping or crusted wounds. Importantly, radiodermatitis can impede cancer treatments. Current treatments for radiodermatitis have shown limited efficacy; thus, improving our understanding of radiodermatitis and developing novel therapies are urgent needs.

Label-free Multiphoton Microscopy Imaging for Guiding the Surgery of Skin Basal Cell Carcinomas

Basal cell carcinoma (BCC) is the most common cancer type. Although it can be surgically removed, to confirm the clean removal by histology is time-consuming, which complicates the treatment and results in many incomplete removals. We propose to develop a special microscopy imaging platform that can image the skin tissue directly without sectioning and staining. This will enable detection of residual tumor cells by examining the excised fresh tissue samples on site during the surgery, providing immediate guidance for improving the treatment procedures.

Endoscopic Laser Raman Spectroscopy for Colorectal Cancer Detection in IBD Patients

Inflammatory Bowel disease (IBD) affects over 200,000 Canadians. Individuals with IBD have significantly greater risk of developing colorectal cancer. Unfortunately, the screening for colorectal cancer that is currently provided to the general population is inadequate for this group. White light colonoscopy is currently the gold standard but is challenging, as lesions are sometimes difficult to identify. Thus, random biopsies, in addition to targeted biopsies of abnormalities visualized by white light, are often performed.

Validation of the Athlete Sleep Screening Questionnaire (ASSQ) in a student-athlete population

The proposed project is designed to address the gaps in knowledge as described above and critical issues by capturing a large amount of student-athlete sleep data using the Athlete Sleep Screening Questionnaire© (ASSQ©), which is a sleep screening questionnaire specifically designed for athletes. It is a highly efficient and convenient tool, given training and travel time constraints where polysomnography, the gold standard of objective sleep measurement is not feasible.

Infrastructure Services Requirement for Sensor based Well-Being Monitor on a Telecommunications Network

Canada population is getting older as the baby boomers enter their retirement years and the current models for communal care will not be able to scale to meet the demand and continuing to age in place and live independently is preferred leading to the best quality of life and outcomes. The recent COVID pandemic experience has made some of the challenges in communal care and provision of remote care clear.

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.

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