Abstract
The application of semi-automated decision support systems in health care faces challenging tasks, mainly in generating evidence based recommendations in a short critical time window. Traditional data collection and survey methodology to generate evidence for the decision support systems also suffers from a slow turn-around time. In addition to probabilistic Bayesian analysis it is required to support reasoning with uncertainty in the context of the total survey error paradigm. Following Jøsang, subjective logic provides a suitable framework for connecting survey data collection directly to a model of evidence based opinions with uncertainty that also support subjective reasoning. We report on the current design and implementation aspects of a system for application of subjective logic to health research surveys.
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Kent, R.D., McCarrell, J., Paquette, G., Amour, B.S., Kobti, Z., Snowdon, A.W. (2010). Application of Subjective Logic to Health Research Surveys. In: Phillips-Wren, G., Jain, L.C., Nakamatsu, K., Howlett, R.J. (eds) Advances in Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 4. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14616-9_37
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DOI: https://doi.org/10.1007/978-3-642-14616-9_37
Publisher Name: Springer, Berlin, Heidelberg
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