PROBES: a framework for probability elicitation from experts.
A decision analytic model represents uncertainties as probability distributions. These distributions are hard to assess especially for large and dynamic models. We propose an integrated framework that facilitates elicitation of the relevant probability distributions for dynamic decision models from...
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sg-smu-ink.sis_research-40362016-02-05T06:30:05Z PROBES: a framework for probability elicitation from experts. Lau, A.H. Tze-Yun LEONG, A decision analytic model represents uncertainties as probability distributions. These distributions are hard to assess especially for large and dynamic models. We propose an integrated framework that facilitates elicitation of the relevant probability distributions for dynamic decision models from the domain experts. The experts usually use some judgmental heuristics to aid probability assessments; the resulting distributions may be proned to cognitive biases. Our framework aims to minimize the effects of these biases and to improve the quality of decisions made. We have implemented a prototype system of the framework and evaluated its effectiveness via a case study in the follow-up management of colorectal cancer patients after curative surgery. Preliminary results demonstrate the practical promise of the framework. 1999-11-10T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/3036 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Colorectal tumor Computer program Decision support system Evaluation Human Probability Recurrent disease Numerical Analysis and Scientific Computing |
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Colorectal tumor Computer program Decision support system Evaluation Human Probability Recurrent disease Numerical Analysis and Scientific Computing Lau, A.H. Tze-Yun LEONG, PROBES: a framework for probability elicitation from experts. |
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A decision analytic model represents uncertainties as probability distributions. These distributions are hard to assess especially for large and dynamic models. We propose an integrated framework that facilitates elicitation of the relevant probability distributions for dynamic decision models from the domain experts. The experts usually use some judgmental heuristics to aid probability assessments; the resulting distributions may be proned to cognitive biases. Our framework aims to minimize the effects of these biases and to improve the quality of decisions made. We have implemented a prototype system of the framework and evaluated its effectiveness via a case study in the follow-up management of colorectal cancer patients after curative surgery. Preliminary results demonstrate the practical promise of the framework. |
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Lau, A.H. Tze-Yun LEONG, |
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Lau, A.H. Tze-Yun LEONG, |
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Lau, A.H. |
title |
PROBES: a framework for probability elicitation from experts. |
title_short |
PROBES: a framework for probability elicitation from experts. |
title_full |
PROBES: a framework for probability elicitation from experts. |
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PROBES: a framework for probability elicitation from experts. |
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PROBES: a framework for probability elicitation from experts. |
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probes: a framework for probability elicitation from experts. |
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Institutional Knowledge at Singapore Management University |
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1999 |
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https://ink.library.smu.edu.sg/sis_research/3036 |
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