PROCEEDINGS IPMU '08
Resolving Public Expert Model Disagreement in Medical Risk Evaluation
A. Grichnik, M. Taylor, C. Nikolopoulos, J. Mason
Medical Risk Stratification (MRS)
models capture the relationships
between modifiable and
unmodifiable factors to help us
understand how various risk
factors jointly contribute to the
likelihood of contracting a disease
in the future. While multiple MRS
models exist for diseases like
cardiovascular disease (CVD) and
diabetes, these models often
conflict with one another when
applied to real-world populations
outside their original study groups.
In this paper we examine the
conflict between public MRS
models of CVD and diabetes and
quantify the disagreement using
both simulated and real-world
populations. A process to resolve
these conflicts is presented and the
resulting improvement in
predictive power is quantified
through Bayesian Posterior
Probability (BPP) analysis of a
population prior to disease onset.
By producing improved MRS
models, we provide valuable
knowledge to those charged with
improving the health of
populations under their care.
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