Recent studies have suggested the role of infection in the development of AD. We used a modified Naïve Bayes model to determine the association between infection and AD. The association was observed with an AROC of 0.72. Several types of infections were identified which had high LRs associated with AD and LRs varied with repetitions as well. The study provides insights about using medical records to identify AD fast and automatically.
Learning Objective 1:
Determine the association between infection and Alzheimer’s Disease and how different categories of infections along with their repetitions impact the risk of developing Alzheimer’s Disease using the extant data in electronic health records.
negin asadzadehzanjani (Presenter)
George Mason University
Sanja Avramovic, George Mason University
Farrokh Alemi, George Mason University