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Framework for guiding artificial intelligence research in combat casualty care
Author(s): Kenneth H. Wong
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Paper Abstract

Combat casualty care is a subfield of emergency medicine that requires intense situational awareness, encyclopedic knowledge, split-second decision making, and high-performing technology. Training medics with these skills requires much time and effort, yet even with the best training, medics can still experience numerous challenges. Artificial intelligence (AI) could offer numerous positive benefits in combat casualty care, but also has significant drawbacks and pitfalls. As a result, there is a vast, multi-dimensional space of possible AI systems and implications to be investigated. Given this context, it would be beneficial to develop a system for guiding research and development efforts in this arena. This paper describes our initial efforts to build a decision-making framework for that purpose. This framework should benefit the field of combat casualty care in at least two ways. First, the framework will support a comprehensive and holistic view of AI applications. Second, it should help to prioritize areas and techniques for research investments.

Paper Details

Date Published: 15 March 2019
PDF: 9 pages
Proc. SPIE 10954, Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications, 109540Q (15 March 2019); doi: 10.1117/12.2512686
Show Author Affiliations
Kenneth H. Wong, Virginia Polytechnic Institute and State Univ. (United States)


Published in SPIE Proceedings Vol. 10954:
Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications
Po-Hao Chen; Peter R. Bak, Editor(s)

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