Using data mining techniques to predict hospitalization of hemodialysis patients
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摘要
Hemodialysis patients might suffer from unhealthy care behaviors or long-term dialysis treatments and need to be hospitalized. If the hospitalization rate of a hemodialysis center is high, its service quality will be low. Therefore, decreasing hospitalization rate is a crucial problem for health care centers. This study combines temporal abstraction with data mining techniques for analyzing dialysis patients' biochemical data to develop a decision support system. The mined temporal patterns are helpful for clinicians to predict hospitalization of hemodialysis patients and to suggest immediate treatments to avoid hospitalization.
论文关键词:Hemodialysis,Temporal abstract,Data mining,Healthcare quality
论文评审过程:Received 20 February 2009, Revised 22 October 2010, Accepted 1 November 2010, Available online 6 November 2010.
论文官网地址:https://doi.org/10.1016/j.dss.2010.11.001