This research applied Bayesian modeling to medication noncompliance
in glaucoma patients. A model-based decision support system using a
Bayesian Network was developed to determine whether a patient was
complying with the medications prescribed by the physician. Results
from this study could potentially improve the decision making
process, given the uncertain and incomplete data available to a
physician. The model may be generalized to other business
situations where a decision has to be made based on incomplete and
uncertain data sets.
Bayesian Networks have increasingly become tools of choice in
solving problems involving uncertainty in the medical domain. These
models have been successfully applied to diagnosis applications.
The purpose of this research was to devise a Bayesian framework to
assess the compliance with medication in glaucoma patients.
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