Kimiko Matsuoka

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The present paper aims at constructing the decision tree for a given database which adopts an improved ID3 decision tree algorithm to implement data mining in order to predict the output. The database is generated using the sampling techniques and the classification algorithm is applied on the samples. The obtained results are compared with experimental(More)
To err is human. How can we avoid near misses and achieve medical safety? From this perspective, we analyzed the nurses' incident data by data mining with the "concept of quality control" that near misses are produced by the system rather than individuals. Nurses' incident data were collected during the 18 months at the emergency room. Significant rules(More)
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