Data Mining Techniques in
Computer-Aided Medical Diagnosis
Widespread
use of medical information systems and explosive growth of medical
databases require methods for efficient computer-assisted analysis.
Diagnosis can be achieved by building a
model of a certain organ under surveillance and comparing it with the
real time physiological measurements taken from the patient. If this
routine is carried out regularly, potential harmful medical conditions
can be detected at an early stage and thus make the process of
combating the disease much easier. This paper presents selected data
mining techniques that can be applied in computer-aided diagnosis,
such as: classification (trees and naïve Bayes), clustering, genetic
algorithms and neural networks. The aim is to provide a theme for
discussions on Data Mining and AI-based methods applied to medicine
