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Prediction of Accident by Using Decision Tree and Display Accident Information

Takahiro Sasaki, Katsutoshi Kanamori, and Hayato Ohwada
Tokyo University of Science, Japan
Abstract—Recently, product accidents have been occurring frequently. We developed a system that predicts injury that is likely to occur and displays accident information in an effort to reduce accidents. To develop this system, we use patient data in the National Electronic Injury Surveillance System (NEISS). NEISS data are collected from hospitals and include such information as how the patient was injured and a description of the situation. We used this information to create decision trees and to display past accident information. The decision tree is used for prediction.

Index Terms—decision tree, Surveillance system, Product accident

Cite: Takahiro Sasaki, Katsutoshi Kanamori, and Hayato Ohwada, "Prediction of Accident by Using Decision Tree and Display Accident Information," Lecture Notes on Information Theory, Vol. 2, No. 2, pp. 186-190, June 2014. doi: 10.12720/lnit.2.2.186-190
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