Applying Data Mining Technology on Sepsis with National Health Insurance Research Database

Yi-Horng Lai

Abstract


Sepsis was a whole-body inflammation caused by an infection. Common signs and symptoms include fever, increased heart rate, increased breathing rate, and confusion. There may also be symptoms related to a specific infection such as a cough with pneumonia or painful urination, with a kidney infection. Sepsis causes and pathogenic mechanism are still not fully grasped by the medical profession. Early symptoms of sepsis are very similar to common diseases. It lead miss the appropriate time of treatment because of ignorant or erroneous diagnosis easily, which lead to serious complications or even death, and also wastes a lot of medical resource. The purpose of this study was to identify characteristics of patients with sepsis and patient’s medical information in the National Health Insurance Research database in Taiwan by using data mining technique in decision tree. The result can be used to assist health care workers to identify the patient groups which have high-risk to suffering from sepsis and progress the prevent strategies.

Keywords


Sepsis, National Health Insurance Research Database (NHIRDB), Data Mining, C5.0 Decision Tree

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References


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