Cite

Abdala, O., & Saeed, M. (2004). Estimation of Missing Values in Clinical Laboratory Measurements of ICU Patients Using a Weighted K-Nearest Neighbors Algorithm. Computers in Cardiology, 31, 693–696.10.1109/CIC.2004.1443033Search in Google Scholar

Adams, K., Uddin, N., & Patterson, J. (2008). Clinical predictors of in-hospital mortality in acutely decompensated heart failure-piecing together the outcome puzzle. Congestive Heart Failure, 14(3), 127–134.10.1111/j.1751-7133.2008.04641.xSearch in Google Scholar

Ajith, A. (2005). Artificial Neural Networks. In P. H. Sydenham & R. Thorn (Eds.), Handbook for Measurement Systems Design (pp. 901–908). London: John Wiley and Sons Ltd.Search in Google Scholar

Arif, M., Akram, M., & Minhas, F. (2010). Pruned fuzzy K-nearest neighbor classifier for beat classification. Journal of Biomedical Science and Engineering, 3(4), 380–389.10.4236/jbise.2010.34053Open DOISearch in Google Scholar

Asi, B., Setarehdan, S., & Mohebbi, M. (2008). Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal. Artificial Intelligence in Medicine, 44(1), 51–64.10.1016/j.artmed.2008.04.007Open DOISearch in Google Scholar

Atoui, H., Fayn, J., Gueyffier, F., & Rubel, P. (2006). Cardiovascular Risk Stratification in Decision Support Systems: A Probabilistic Approach. Application to Health. Computers in Cardiology, 33, 218–284.Search in Google Scholar

Bagley, S., White, H., & Golomb, B. (2001). Logistic regression in the medical literature: Standards for use and reporting, with particular attention to one medical domain. Journal of Clinical Epidemiology, 54(10), 979–985.10.1016/S0895-4356(01)00372-9Search in Google Scholar

Bairstow, P., Persaud, J., Mendelson, R., & Ngyuen, L. (2010). Reducing inappropriate diagnostic practice through education and decision support. International Journal for Quality in Health Care, 22(3), 194–200.10.1093/intqhc/mzq016Open DOISearch in Google Scholar

Bates, D., Kuperman, G., Wang, S., Gandhi, T., Kittler, A., Volk, L., Spurr, C., et al. (2006). Ten commandments for effective clinical decision support: making the practice of evidence-based medicine a reality. Journal of the American Medical Informatics Association, 10(6), 523–530.10.1197/jamia.M1370Open DOISearch in Google Scholar

Berlin, A., Sorani, M., & Sim, I. (2006). A taxonomic description of computer-based clinical decision support systems. Journal of Biomedical Informatics, 39(6), 656–667.10.1016/j.jbi.2005.12.003Open DOISearch in Google Scholar

Berner, E. S. (Ed.). (1999). Clinical decision support systems: theory and practice (pp. 3–30). Germany: Springer.10.1007/978-1-4757-3903-9Search in Google Scholar

Berner, E. S. (Ed.). (2009). Clinical Decision Support Systems: State of the Art (AHRQ Publication No. 09-0069-EF). Rockville, Maryland: Agency for Healthcare Research and Quality.Search in Google Scholar

Birkmeyer, J., Schwartz, L., Sargent, J., & Woloshin, S. (2001). Computer-Based Decision Support. Wishing on a Star? Effective Clinical Practice, 4(1), 34–38.10.1109/MC.2001.970555Search in Google Scholar

Chen, S., Hsiao, Y., Huang, Y., Kupo, S., Tseng, H., Wu, H., & Chen, D. (2009). Comparative Analysis of Logistic Regression, Support Vector Machine and Artificial Neural Network for the Differential Diagnosis of Benign and Malignant Solid Breast Tumors by the Use of Three-Dimensional Power Doppler Imaging. Korean Journal of Radiology, 10(5), 464–471.10.3348/kjr.2009.10.5.464Open DOISearch in Google Scholar

Colantonio, S., Martinelli, M., Moroni, D., Salvetti, O., Perticone, F., Sciacqua, A., Conforti, D., & Gualtieri, A. (2007). An approach to decision support in heart failure. CEUR Workshop Proceedings, 314, 1–10.Search in Google Scholar

Comak, E., Arslan, A., & Türkoglu, I. (2007). A decision support system based on support vector machines for diagnosis of the heart valve diseases. Computers in Biology and Medicine, 37(1), 21–27.10.1016/j.compbiomed.2005.11.002Open DOISearch in Google Scholar

Dobbson, A. (1983). The role of Statistician. International Journal of Epidemiology, 12(3), 274–275.10.1093/ije/12.3.274Open DOISearch in Google Scholar

Dolan, J. (2008). Shared decision-making – transferring research into practice: the Analytic Hierarchy Process (AHP). Patient Education and Counseling, 73(3), 418–425.10.1016/j.pec.2008.07.032Search in Google Scholar

Durieux, P., Nizard, R., Ravaud, P., Mounier, N., & Lepage, E. (2000). A clinical decision support system for prevention of venous thromboembolism: effect on physician behavior. JAMA, 283(21), 2816–2821.10.1001/jama.283.21.2816Search in Google Scholar

Eom, J., Kim, S., & Zhang, B. (2008). AptaCDSS-E: A classifier ensemble-based clinical decision support system for cardiovascular disease level prediction. Expert Systems with Applications, 34(4), 2465–2479.10.1016/j.eswa.2007.04.015Open DOISearch in Google Scholar

Fonarow, G. (2008). Epidemiology and risk stratification in acute heart failure. American Heart Journal, 155(2), 200–207.10.1016/j.ahj.2006.10.043Search in Google Scholar

Fonarow, G., Adams, K., Abraham, W., Yancy, C., & Boscardin, W. (2005). Risk Stratification for In-Hospital Mortality in Acutely Decompensated Heart Failure – classification and regression tree analysis. JAMA, 293(5), 572–580.10.1001/jama.293.5.572Search in Google Scholar

Forsström, J., & Dalton, K. (1995). Artificial neural networks for decision support in clinical medicine. Annals of Medicine, 27(5), 509–517.10.3109/07853899509002462Open DOISearch in Google Scholar

Garg, A., Adhikari, N., McDonald, H., Rosas-Arellano, M., Devereaux, P., Beyene, J., & Haynes, R. (2005). Effects of computerized clinical decision support systems on practitioner performance and patient outcomes. A Systematic Review. JAMA, 293(10), 1223–1238.10.1001/jama.293.10.1223Search in Google Scholar

Gencer, B., Vaucher, P., Herzig, L., Verdon, F., Ruffieux, C., Bösner, S., & Favrat, B. (2010). Rulling out coronary heart disease in primary care patients with chest pain: a clinical prediction score. BMC Medicine, 8(9), 1–10.10.1186/1741-7015-8-9Open DOISearch in Google Scholar

Glaser, J. (2008). Clinical decision support: the power behind the electronic health record. Healthcare Financial Management, 62(7), 50–51.Search in Google Scholar

Guilan, K., Dong-Ling, X., & Jian-Bo, Y. (2008). Clinical decision support systems: a review on knowledge representation and inference under uncertainties. International Journal of Computational Intelligence Systems, 1(2), 159–167.10.1080/18756891.2008.9727613Search in Google Scholar

Hardy, D., & Smith, D. (2008). Decision making in clinical practice. British Journal of Anaesthetic & Recovery Nursing, 9(1), 19–21.10.1017/S1742645608000028Search in Google Scholar

Haynes, R., & Wilczyński, N. (2010). Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: Methods of a decision maker-research partnership systemic review. Implementation Science, 5:12.10.1186/1748-5908-5-12Search in Google Scholar

Hossain, M., Wright, S., & Pertersen, L. (2002). Comparing performance of multi-nomial logistic regression and discriminant analysis for monitoring access to care for acute myocardial infarction. Journal of Clinical Epidemiology, 55(4), 400–406.10.1016/S0895-4356(01)00505-4Open DOISearch in Google Scholar

Huang, D., Quan, Y., He, M., & Zhou, B. (2009). Comparison of linear discriminant analysis methods for the classification of cancer based on gene expression data. Journal of Experimental & Clinical Cancer Research, 28(1), 149–156.10.1186/1756-9966-28-149Open DOISearch in Google Scholar

Hughes, M. C. (2009). Using clinical decision support to improve health and achieve cost savings (Anvita Health Report). Retrieved from http://anvitahealth.com/...pdf/AnvitaHealth20Report-CDSROI.pdfSearch in Google Scholar

Jankowski, S., Szymański, Z., Piątkowska-Janko, E., & Oreziak, A. (2007). Improved recognition of sustained ventricular tachycardia from SAECG by support vector machine. The Anatolian Journal of Cardiology, 7(Suppl 1), 112–115.Search in Google Scholar

Ji, S., Smith, R., Huynh, T., & Najarian, K. (2009). A comparative analysis of multi–level computer-assisted decision making systems for traumatic injuries. BMC Medical Informatics and Decision Making, 9:2, 2–18.10.1186/1472-6947-9-2Search in Google Scholar

Jilani, T., Yasin, H., Yasin, M., & Ardil, C. (2013). Acute coronary syndrome prediction using data mining techniques – an application. World Academy of Science, Engineering and Technology, International Journal of Computer and Information Engineering, 7(1), 168–172.Search in Google Scholar

Kawamoto, K., Houlihan, C., Balas, E., & Lobach, D. (2005). Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ, 330(7494), 765–772.10.1136/bmj.38398.500764.8FSearch in Google Scholar

Kurt, I., Ture, M., & Kurum, A. (2008). Comparing performances of logistic regression, classification and regression tree, and neural networks for predicting coronary artery disease. Expert Systems with Applications, 34(1), 366–374.10.1016/j.eswa.2006.09.004Search in Google Scholar

Lenz, R., & Reuchert, M. (2007). IT support for healthcare process – premises, challenges, perspectives. Data & Knowledge Engineering, 61, 39–58.10.1016/j.datak.2006.04.007Search in Google Scholar

Leslie, L., & Denvir, M. (2007). Clinical decision support software for chronic heart failure. Critical Pathways in Cardiology: A Journal of Evidence-Based Medicine, 6(3), 121–126.10.1097/HPC.0b013e31812da7ccSearch in Google Scholar

Levy, W., & Linker, D. (2008). Prediction of Mortality in Patients with Heart Failure and Systolic Dysfunction. Current Cardiology Report, 10(3), 198–205.10.1007/s11886-008-0034-0Search in Google Scholar

Lin, C., Lin, C., Lin, B., & Yang, M. (2009). A decision support system for improving doctor’s prescribing behavior. Expert Systems with Applications, 36(4), 7975–7984.10.1016/j.eswa.2008.10.066Open DOISearch in Google Scholar

Lindgaard, G., Pyper, C., Frize, M., & Walker, R. (2009). Does Bayes have it? Decision Support Systems in diagnostic medicine. International Journal of Industrial Ergonomics, 39(3), 524–532.10.1016/j.ergon.2008.10.011Open DOISearch in Google Scholar

Lisboa, P., & Taktak, A. (2006). The use of artificial neural networks in decision support in cancer: A systematic review. Neural Networks, 19(4), 408–415.10.1016/j.neunet.2005.10.007Open DOISearch in Google Scholar

Long, W., Griffith, L., Selker, H., & D’Agostino, R. (1993). A comparison of logistic regression to decision-tree induction in a medical domain. Computers in Biomedical Research, 26(1), 74–97.10.1006/cbmr.1993.1005Search in Google Scholar

Mahesh, V., Kandaswamy, A., Vimal, C., & Sathish, B. (2009). ECG arrhythmia classification based on logistic model tree. Journal of Biomedical Science and Engineering, 2(6), 405–411.10.4236/jbise.2009.26058Open DOISearch in Google Scholar

Martí, V., Ballester, M., Marrugat, J., Auge, J., Padro, J., Narula, J., & Car-alps, J. (1997). Assessment of the appropriateness of the decision of heart transplantation in idiopathic-dilated cardiomyopathy. The American Journal of Cardiology, 80(6), 746–750.10.1016/S0002-9149(97)00507-9Open DOISearch in Google Scholar

Montgomery, A., Fahey, T., Peters, T., MacIntosh, C., & Sharp, D. (2000). Evaluation of computer based clinical decision support system and risk chart for management of hypertension in primary care: randomised controlled trial. BMJ, 320(7236), 686–690.10.1136/bmj.320.7236.686Search in Google Scholar

Musen, M. A. (1997). Methods for decision support. In M. A. Musen & J. H. van Bemel (Eds.), Handbook of medical informatics (pp. 233–246). Germany: Springer.Search in Google Scholar

Ortiz, J., Ghefter, C., Silva, C., & Sabbatini, R. (1995). One-year mortality prognosis in heart failure: A neural network approach based on echocardiographic data. Journal of the American College of Cardiology, 26(7), 1586–1593.10.1016/0735-1097(95)00385-1Open DOISearch in Google Scholar

Pavlopoulos, S., Stasis, A., & Loukis, E. (2004). A decision tree-based method for the differential diagnosis of Aortic Stenosis from Mitral Regurgitation using heart sounds. BioMedical Engineering Online, 3:21, 21–35.10.1186/1475-925X-3-21Search in Google Scholar

Philips, K., & Street, W. (2005). Predicting outcomes of hospitalization for heart failure using logistic regression and knowledge discovery methods. In AMIA 2005 Annual Symposium Proceedings (pp. 1080).Search in Google Scholar

Polat, K., & Günes, S. (2006). A hybrid medical decision making system based on principles component analysis, k-NN based weighted pre-processing and adaptive neuro fuzzy inference system. Digital Signal Processing, 16(6), 913–921.10.1016/j.dsp.2006.05.001Open DOISearch in Google Scholar

Ragab, A., Fakeeh, K., & Roushdy, M. (2004). A medical multimedia expert system for heart diseases diagnosis and treatment. In Proceedings of the 2nd Saudi Science Conference (pp. 31–45). Jeddah, Kingdom of Saudi Arabia.Search in Google Scholar

Rausch, J., & Kelley, K. (2009). A comparison of linear and mixture models for discriminant analysis under abnormality. Behavior Research Methods, 41(1), 85–98.10.3758/BRM.41.1.85Open DOISearch in Google Scholar

Raut, R., & Dudul, S. (2010). Intelligent diagnosis of heart diseases using neural network approach. International Journal of Computer Applications, 1(2), 117–123.10.5120/31-140Search in Google Scholar

Reisman, Y. (1996). Computer-based clinical decision aids. A review of methods and assessment of systems. Medical Informatics, 21(3), 179–197.10.3109/14639239609025356Open DOISearch in Google Scholar

Setiawan, N., Venkatachalam, P., & Hani, A. (2009). Diagnosis of coronary artery disease using artificial intelligence based decision support system. In Proceedings of the International Conference on Man-Machine Systems (pp. 1C3-1-1C3-5). Batu Ferringhi, Penang, MalaysiaSearch in Google Scholar

Shantakumar, B., & Kumaraswamy, Y. (2009). Intelligent and effective heart attack prediction system using data mining and artificial neural networks. European Journal of Scientific Research, 31(4), 642–656.Search in Google Scholar

Shanti, D., Sahoo, G., & Saravanan, N. (2009). Designing an artificial neural network model for the prediction of thrombo-embolic stroke. International Journal of Biometrics and Bioinformatics, 3(1), 10–18.Search in Google Scholar

Sim, I., Gorman, P., Greenes, R., Haynes, R., Kaplan, B., Lehmann, H., & Tang, P. C. (2001). Clinical decision support systems for the practice of evidence-based medicine. Journal of the American Medical Informatics Association, 8(6), 527–534.10.1136/jamia.2001.0080527Open DOISearch in Google Scholar

Sintchenko, V., Iredell, J., Gilbert, G., & Coiera, E. (2005). Handheld computer-based decision support reduces patient length of stay and antibiotic prescribing in critical care. Journal of the American Medical Informatics Association, 12(4), 398–402.10.1197/jamia.M1798Open DOISearch in Google Scholar

Szydło, R. (2005). Komu jest potrzebny statystyk medyczny? Onkologia w Praktyce Klinicznej, 1(3), 129–131.Search in Google Scholar

Thursky, K., Buising, K., Bak, N., Macgregor, L., Street, A., Macintyre, C., Brown, G., et al. (2006). Reduction of broad-spectrum antibiotic use with computerized decision support in an intensive care unit. International Journal for Quality in Health Care, 18(3), 224–231.10.1093/intqhc/mzi095Open DOISearch in Google Scholar

Tierney, W. (2001). Improving clinical decision and outcomes with information: a review. International Journal of Medical Informatics, 62(1), 1–9.10.1016/S1386-5056(01)00127-7Search in Google Scholar

Verplancke, T., Van Looy, S., Benoit, D., Vansteelandt, S., Depuydt, P., De Turck, F., & Decruyenaere, J. (2008). Support vector machine versus logistic regression modeling for prediction of hospital mortality in critically ill patients with haematological malignancies. BMC Medical Informatics and Decision Making, 8:56.10.1186/1472-6947-8-56Search in Google Scholar

Wang, T., Jang, T., Huang, C., Kao, S., Lin, C., Lee, F., Liu, C., et al. (2004). Establishing a clinical decision rule of severe acute respiratory syndrome at the emergency department. Annals of Emergency Medicie, 43(1), 17–22.10.1016/j.annemergmed.2003.08.002Search in Google Scholar

Wennberg, J. (1988). Improving the medical decision-making process. Health Affairs, 7(1), 99–106.10.1377/hlthaff.7.1.99Open DOISearch in Google Scholar

Young, A. S., Chaney, E., Shoai, R., Bonner, L., Cohen, A. N., Doebbeling, B., Dorr, D., et al. (2007). Information technology to support improved care for chronic illness. Journal of General Internal Medicine, 22(Suppl. 3), 425–430.10.1007/s11606-007-0303-4Open DOISearch in Google Scholar

Zupan, B., Porenta, A., Vidmar, G., Aoki, N., Bratko, I., & Beck, J. (2001). Decision at hand: a decision support system on handhelds. Studies in Health Technology and Informatics, 84(1), 566–570.Search in Google Scholar

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