Source: Ann. Appl. Stat.
Volume 6, Number 2
We propose a statistical modeling technique, called the
Hierarchical Association Rule Model (HARM), that predicts a
patient’s possible future medical conditions given the patient’s
current and past history of reported conditions. The core of our
technique is a Bayesian hierarchical model for selecting
predictive association rules (such as “condition 1 and
condition 2 → condition 3”) from a large
set of candidate rules. Because this method “borrows strength”
using the conditions of many similar patients, it is able to
provide predictions specialized to any given patient, even when
little information about the patient’s history of conditions is
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