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We propose a statistical modeling technique, called the HierarchicalAssociation Rule Model (HARM), that predicts a patient's possible futuremedical conditions given the patient's current and past history of reportedconditions. The core of our technique is a Bayesian hierarchical model forselecting predictive association rules (such as "condition 1 and condition 2$\rightarrow$ condition 3") from a large set of candidate rules. Because thismethod "borrows strength" using the conditions of many similar patients, it isable to provide predictions specialized to any given patient, even when littleinformation about the patient's history of conditions is available.

Bayesian hierarchical rule modeling for predicting medical conditions