Rough Sets: A Knowledge Discovery Technique for Multifactorial Medical Outcomes

Rough sets is a fairly new and promising technique for data mining and knowledge discovery from databases. Most introductory articles to rough sets are highly technical and mathematically oriented. This tutorial paper presents the fundamentals of rough set theory in a non-technical manner, and outlines how the technique can be used to extract minimal if-then rules from tables of empirical data that either fully or approximately describe given example classifications. Since such rules are readily interpretable, they can be inspected in order to yield possible new insight into how various contributing factors interact, and thus serve as hypothesis-generators for further research. Additionally, the set of mined rules may function as a classifier of new, unseen cases. An example application for prediction of ambulation for patients with spinal cord injury is given. Keywords: rough sets, data mining, knowledge discovery, machine learning, classification, modeling, outcome, prognosis, ambul..