TY - JOUR
T1 - Evaluation of rule interestingness measures in medical knowledge discovery in databases
AU - Ohsaki, Miho
AU - Abe, Hidenao
AU - Tsumoto, Shusaku
AU - Yokoi, Hideto
AU - Yamaguchi, Takahira
PY - 2007/11
Y1 - 2007/11
N2 - Objective: We discuss the usefulness of rule interestingness measures for medical KDD through experiments using clinical datasets, and, based on the outcomes of these experiments, also consider how to utilize these measures in postprocessing. Methods and materials: We first conducted an experiment to compare the evaluation results derived from a total of 40 various interestingness measures with those supplied by a medical expert for rules discovered in a clinical dataset on meningitis. We calculated and compared the performance of each interestingness measure to estimate a medical expert's interest using f-measure and correlation coefficient. We then conducted a similar experiment for hepatitis. Results and conclusion: The comprehensive results of experiments on meningitis and hepatitis indicate that the interestingness measures, accuracy, chi-square measure for one quadrant, relative risk, uncovered negative, and peculiarity, have a stable, reasonable performance in estimating real human interest in the medical domain. The results also indicate that the performance of interestingness measures is influenced by the certainty of a hypothesis made by the medical expert, and that the combinational use of interestingness measures will contribute to support medical experts to generate and confirm their hypotheses through human-system interaction.
AB - Objective: We discuss the usefulness of rule interestingness measures for medical KDD through experiments using clinical datasets, and, based on the outcomes of these experiments, also consider how to utilize these measures in postprocessing. Methods and materials: We first conducted an experiment to compare the evaluation results derived from a total of 40 various interestingness measures with those supplied by a medical expert for rules discovered in a clinical dataset on meningitis. We calculated and compared the performance of each interestingness measure to estimate a medical expert's interest using f-measure and correlation coefficient. We then conducted a similar experiment for hepatitis. Results and conclusion: The comprehensive results of experiments on meningitis and hepatitis indicate that the interestingness measures, accuracy, chi-square measure for one quadrant, relative risk, uncovered negative, and peculiarity, have a stable, reasonable performance in estimating real human interest in the medical domain. The results also indicate that the performance of interestingness measures is influenced by the certainty of a hypothesis made by the medical expert, and that the combinational use of interestingness measures will contribute to support medical experts to generate and confirm their hypotheses through human-system interaction.
KW - 68T30
KW - 68U35
KW - Clinical data
KW - Data mining
KW - Interestingness
KW - Knowledge discovery in databases
KW - Postprocessing
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U2 - 10.1016/j.artmed.2007.07.005
DO - 10.1016/j.artmed.2007.07.005
M3 - Article
C2 - 17851054
AN - SCOPUS:35648950495
VL - 41
SP - 177
EP - 196
JO - Artificial Intelligence in Medicine
JF - Artificial Intelligence in Medicine
SN - 0933-3657
IS - 3
ER -