DIMACS TR: 2002-11
Coronary Risk Prediction by Logical Analysis of Data
Authors: Sorin Alexe, Eugene Blackstone, Peter L. Hammer, Hemant Ishwaran, Michael S. Lauer, Claire E. Pothier Snader
ABSTRACT
The objective of this study was to distinguish within a population
of patients with known or suspected coronary artery disease groups at high
and at low mortality rates. The study was based on Cleveland Clinic
Foundation's dataset of 9454 patients, of whom 312 died during an
observation period of 9 years. The Logical Analysis of Data method was
adapted to handle the disproportioned size of the two groups of patients,
and the inseparable character of this dataset -- characteristic to many
medical problems. As a result of the study, we have identified a high-risk
group of patients representing 1/5 of the population, with a mortality
rate 4 times higher than the average, and including 3/4 of the patients
who died. The low-risk group identified in the study, representing
approximately 4/5 of the population, had a mortality rate 3 times lower
than the average.
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