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\iteman{io-port 05838420}
\itemau{Ali, Shahriyah Nyak Saad; Razali, Ahmad Mahir; Bakar, Azuraliza Abu; Suradi, Nur Riza}
\itemti{Developing treatment plan support in outpatient health care delivery with decision trees technique.}
\itemso{Cao, Longbing (ed.) et al., Advanced data mining and applications. 6th international conference, ADMA 2010, Chongqing, China, November 19--21, 2010. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-17312-7/pbk). Lecture Notes in Computer Science 6441. Lecture Notes in Artificial Intelligence, 475-482 (2010).}
\itemab
Summary: This paper presents treatment plan support (TPS) development with the aim to support treatment decision making for physicians during outpatient-care giving to patients. Evidence-based clinical data from system database was used. The TPS predictive modeling was generated using decision trees technique, which incorporated predictor variables: patient's age, gender, racial, marital status, occupation, visit complaint, clinical diagnosis and final diagnosed diseases; while dependent variable: treatment by drug, laboratory, imaging and/or procedure. Six common diseases which are coded as J02.9, J03.9, J06.9, J30.4, M62.6 and N39.0 in the International Classification of Diseases $10^{\text{th}}$ Revision (ICD-10) by World Health Organization were selected as prototypes for this study. The good performance scores from experimental results indicate that this study can be used as guidance in developing support specifically on treatment plan in outpatient health care delivery.
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\itemut{User acceptance; Continuous quality improvement; Treatment equity}
\itemli{doi:10.1007/978-3-642-17313-4\_47}
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