چکیده (انگلیسی):

Knowledge discovery is one of the vital fields which strongly
supports decision making by applying different techniques based on the
targeted field and the required information. Focusing on clustering and
classification techniques, this paper presents an approach for adapting
one of the classification algorithms for supporting decision making
procedure in radiology data analysis field. The proposed adaptation is
based on dividing the analysis problem by data partitioning and
individually examining against each cluster, with applying the
classification algorithm in a parallel approach. The proposed approach
has proved to produce higher results accuracy with minimization of
time when compared with the traditional ID3.