Book Summary:
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. 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. |