When the Virtual Becomes Reality: An Environmental Scan of the Presence of Virtual Reality and Artificial Intelligence in Health and Cancer Care Environments

Grey literature has long been associated with technological enhancements, recognizing the power that informational communication, namely, social media, plays in generating interest in blogs, Twitter feeds, and other instantaneous knowledge exchange platforms. The ability of these programs to generate and identify specific data patterns1 from a single posting has led to increasing interest in two aspects of machine learning in health care, namely Artificial Intelligence (AI) and Virtual Reality (VR).1 AI “mimics elements of human cognition by computational means”1, whereas VR enhances this cognition by allowing users to interact with a “three-dimensional, computer generated environment”2, manipulating objects and scenarios in an artificial world2. Introduced as a form of grey literature via Second Life3, a popular role-playing online world launched in 2003, VR and AI have had a visible presence in numerous sectors, including healthcare.4 In 2011, IBM created Watson, a supercomputer considered to be one of the most revolutionary breakthrough’s in artificial intelligence4. To test this claim, Watson appeared on an episode of Jeopardy, one of the longest-running game shows in the United States, in a friendly competition match between two of the winningest contestants in the show’s 50 year history4. Watson’s emphatic victory over the human contestants drew increasing interest to other applications of artificial intelligence and virtual reality, specifically in the field of healthcare. While the first use of AI and VR in medicine is believed to have occurred in the 1990s for interpreting electrocardiograms4, the invention of cloud networking in 20064 is considered the first proven use of AI and VR in the modern era focusing on healthcare. Although the arguments for AI and VI in clinical settings are plentiful, ranging from enhancing imaging and increased processing speed in electronic medical record (EMR) applications4, the scenario is less clear-cut within the environment of cancer care. At the 2016 International Symposium of Biomedical Imaging in Prague, a joint team of scientists and engineers claimed that the use of artificial intelligence resulted in a “92% accuracy [rate of detection] in breast tissue cancer cells5.” However, a column authored in 2017 disputed a claim by IBM that Watson was the new revolution to cancer care6. This paper will aim to shed light on how artificial intelligence and virtual reality is viewed in both health and cancer care fields via a two-fold environmental scan approach, namely an anonymous survey polling staff working at two cancer care facilities in Calgary, Alberta, Canada, asking respondents to comment on any papers they have ever encountered in their own practice/research discussing AI or VR. This practice will be supplemented with a comprehensive search through the academic literature to achieve a hoped-for grand total of 50 unique papers. Each of these papers will be analyzed via the use of Altmetrics, “a single research output [that] can be talked about across dozens of different platforms”7, a methodology introduced by Schopfel and Prost at GL 18, to determine how these perceived core papers are being shared via the use of social media. References 1. Rubak, J. (2018). Introduction to machine learning. Presented March 1, 2018 at the Tom Baker Cancer Centre [medical physicists session] 2. Virtual Reality Society. (2017). What is virtual reality? Retrieved March 3, 2018 from https://www.vrs.org.uk/virtual-reality/what-is-virtual-reality.html 3. Ferry, K., Gelfand, J., Peterman, D., & Tomren, H. (2008). Virtual reality and establishing a presence in Second Life: new forms of grey literature? The Grey Journal, 4(3): 159-168. 4. Miller, D., & Brown, E. (2018). Artificial intelligence in medical practice: the question to the answer? The American Journal of Medicine, 131: 129-133. 5. Moore, C. (2016). Artificial intelligence gets an A+ for accuracy diagnosing breast cancer. Retrieved March 23, 2018 from https://breastcancer-news.com/2016/06/29/artificial-intelligence-gets-accuracy-diagnosing-breast-cancer/ 6. Ross, C., & Swetlitz, I. (2017). IBM pitched its Watson supercomputer as a revolution in cancer care. It’s nowhere close. Retrieved March 23, 2018 from https://www.statnews.com/2017/09/05/watson-ibm-cancer/ 7. Schopfel, J., & Prost, H. (2016). Altmetrics and grey literature: perspectives and challenges. The Grey Journal, 13(1): 5-22.

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