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 10th 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. © 2010 Springer-Verlag.
CITATION STYLE
Ali, S. N. S., Razali, A. M., Bakar, A. A., & Suradi, N. R. (2010). Developing treatment plan support in outpatient health care delivery with decision trees technique. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6441 LNAI, pp. 475–482). https://doi.org/10.1007/978-3-642-17313-4_47
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