The ultimate purpose of many medical data mining systems is to create formalized
knowledge for a computer-aided diagnostic system, which can in turn, provide a second …

Data-mining methods can be used to generate rules, or identify patterns, from medical data
to assist clinical diagnosis and decision-making. However, in the initial stages of a clinical …

Discusses eliminating contradictions among rules in computer-aided systems, experts rules,
and databases. The study has demonstrated how consistent data mining in medical …

Widespread use of medical information systems and explosive growth of medical databases
require traditional manual data analysis to be coupled with methods for efficient computer …

In sequential diagnosis, the usefulness of a test can be assessed only in the context of a
chosen diagnostic strategy, and depends on the evidence provided by previous test results …

Data mining is a process of pattern and relationship discovery within large sets of data. The
context encompasses several fields, including pattern recognition, statistics, computer …

The development of computers has provided a potential tool to assist in the management of
the information explosion in medicine. The field of medical diagnosis is intellectually …

The process of automatically extracting novel, useful and ultimately comprehensible
information from large databases, known as data mining, has become of great importance …

A methodology forthe modeling of large data sets is described which results in rule sets
having minimal inter-rule interactions, and being simply maintained. An algorithm for …

We propose a methodology, based on Computer Algebra and implemented in CoCoA
language, for constructing rule based expert systems, that can be applied to the diagnosis of …