Ms. Kaleigh Johnson-Cover

HBSc. Biomedical Science, HBSc. Biomedical Science

Affiliations: Supported Learning Groups, University of Guelph

Program Assistant , Neurofeedback Mentor , Program Assistant , Neurofeedback Mentor

Research Interests:

- Design thinking in higher education - Supplemental instruction - Knowledge translation - Implementation science - Operations research - Healthcare engineering - Health literacy Previous research: the role of the endocannabinoid system and the neural mechanisms of nausea; the pathophysiology of multiple sclerosis as it relates to calcium homeostasis in the central nervous system

Brief Bio:

Design thinker, knowledge translator, lifelong learner. Working to expand my creative skillset as a means to pursue tangible, positive impact in my community through collaboration and innovation. Let's chat!

Capstone Project:

As technology advances and the use of artificial intelligence (AI) technology is adopted in various fields, there are increasing efforts to develop AI technology for healthcare applications to improve care delivery and patient outcomes. However, there are few examples of AI technology currently being used in clinical settings. Thus in the formation of this project, the team wanted to understand why this disparity exists.

The application of AI technologies in the healthcare sector has been of great interest in recent years. There have been significant investments made into developing these technologies (Murphy, 2017; Silcoff, 2018; KPMG, 2018), and AI in healthcare has been the topic of numerous conferences (O’Neil, 2017), editorial commentaries (Beam & Kohane, 2016; Norrie, 2018; Naylor, 2018; Hinton, 2018), and news blogs (Siwicki, 2017; Siwicki, 2019; Towers-Clark, 2018; HIMSS, 2018). Of the many possible applications, the use of ML technology to generate predictions to inform medical decision-making has incited discussion of the implications on the health system (Kuziemsky, 2016; Shahid et al., 2019). Extensive research and development has been conducted for AI technology for healthcare, however there remain few examples of successful AI implemented in health settings (Lancet, 2018).

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