Clinical Decision Support System for Hypertension Management
نویسندگان
چکیده
This study examined the predictive power of data mining algorithms by comparing the performance of a logistic regression algorithm with that of a decision tree algorithm called CHAID (Chi-squared Automatic Interaction Detection). Unlike in the previous studies, the decision tree performed better than logistic regression. This paper also demonstrated how another data mining model, called association rule, could be used in validating clinical decision rules for hypertension management. We also developed a CDSS (Clinical Decision Support System) with three modules (doctor, nurse, and patient) based on data warehouse architecture. This system can help improve doctors’ decisionand can make educational material more accessible to patients.
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