This study adopted an integrated procedure that combines
the clustering and classification features of data mining
technology to determine the differences between the symptoms
shown in past cases where patients died from or survived oral
cancer. Two datamining tools, namely decision tree and artificial
neural network, were used to analyze the historical cases of oral
cancer, and their performance was compared with that of logistic
regression, the popular statistical analysis tool. Both decision tree
and artificial neural network models showed superiority to the
traditional statistical model. However, as to clinician, the trees
created by the decision tree models are relatively easier to interpret
compared to that of the artificial neural network models.
Cluster analysis also discovers that those stage 4 patients whose
also possess the following four characteristics are having an
extremely low survival rate: pN is N2b, level of RLNM is level
I-III, AJCC-T is T4, and cells mutate situation (G) is moderate.