  This survey reviews several approaches of data mining (DM) in healthindustry
from many research groups world wide. The focus is on modern multi-core
processors built into today's commodity computers, which are typically found at
university institutes both as small server and workstation computers. So they
are deliberately not high-performance computers. Modern multi-core processors
consist of several (2 to over 100) computer cores, which work independently of
each other according to the principle of "multiple instruction multiple data"
(MIMD). They have a common main memory (shared memory). Each of these computer
cores has several (2-16) arithmetic-logic units, which can simultaneously carry
out the same arithmetic operation on several data in a vector-like manner
(single instruction multiple data, SIMD). DM algorithms must use both types of
parallelism (SIMD and MIMD), with access to the main memory (centralized
component) being the main barrier to increased efficiency. This is important
for DM in healthindustry applications like ECG, EEG, CT, SPECT, fMRI, DTI,
ultrasound, microscopy, dermascopy, etc.
