AAAI Publications, 2014 AAAI Spring Symposium Series

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Arresting Treatment Patterns for Individual Patients in Clinical Big Data: An Exploratory Procedure
Mizuki Morita, Masanori Shiro, Shotaro Akaho, Hideki Asoh, Toshihiro Kamishima, Eiji Aramaki, Koiti Hasida, Takahide Kohro

Last modified: 2014-03-22

Abstract


Data mining of clinical data that are stored continually in the course of daily medical practice will contribute to the advancement of healthcare. However, real-world clinical data are characteristically noisy, sparse, and irregular, which makes it difficult to perform data mining. This study assesses an exploratory approach to ascertain how physicians tackle the worsening of a patient's condition using clinical data from a hospital. It yielded reasonable results.

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