Advanced SearchSearch Tips
Network Identification of Major Risk Factor Associated with Delirium by Bayesian Network
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Network Identification of Major Risk Factor Associated with Delirium by Bayesian Network
Lee, Jea-Young; Choi, Young-Jin;
  PDF(new window)
We analyzed using logistic to find factors with a mental disorder because logistic is the most efficient way assess risk factors. In this paper, we applied data mining techniques that are logistic, neural network, c5.0, cart and Bayesian network to delirium data. The Bayesian network method was chosen as the best model. When delirium data were applied to the Bayesian network, we determined the risk factors associated with delirium as well as identified the network between the risk factors.
Bayesian network;data mining;delirium mental disorder;
 Cited by
베이지안 네트워크와 방사형 그래프를 이용한 섬망의 효과 규명,이제영;배재영;

Journal of the Korean Data and Information Science Society, 2011. vol.22. 5, pp.911-919
베이지안 네트워크를 활용한 정신장애 질병 섬망의 주요 위험인자와 오즈비,이제영;최영진;

Journal of the Korean Data and Information Science Society, 2011. vol.22. 2, pp.217-225
An Approach for R&D Partner Selection in Alliances between Large Companies, and Small and Medium Enterprises (SMEs): Application of Bayesian Network and Patent Analysis, Sustainability, 2016, 8, 12, 117  crossref(new windwow)
김경헌 (2005). 베이지안 네트웨크에 기초한 백혈병 유전자데이터의 분석, B.I. Thesis 1-15.

이용원 (2004). 고혈압의 위험요인에 대한 데이터 마이닝 모형 분석 - 종합건강검진 데이터를 바탕으로, M.S.Thesis 1-52.

이재원, 박미라, 유한나 (2005). <생명과학연구를 위한 통계적 방법>, 자유아카데미, 서울.

허명회, 이용구(2008). <데이터마이닝 모델링과 사례>, 한나래, 서울.

Arend, E. and Christensen, M. (2009). Delirium in the intensive care unit: A review, British Association of Critical Care Nurses, Nursing in Critical Care, 14, 145-154. crossref(new window)

Breiman, L., Friedman, J., Olshen, R. and Stone, C. (1984). Classification and Decision Tree, Chapman & Hall.

Cole, M. and Primeau, F. (1993). Prognosis of delirium in elderly hospital patients, Canadian Medical Association Journal, 149, 41-46.

Dubois, M., Strobik, Y., Bergeron, N., Dumont, M. and Dial, S. (2001). Delirium in an intensive care unit: A study of risk factors, Intensive Care Medicine, 27, 1297-1304. crossref(new window)

Heckerman, D. (1995). A tutorial on learning with Bayesian networks, Technical Report MSR-TR-95-06, Microsoft Research, 1-58.

Heckerman, D. (1997). Bayesian Networks for Data Mining, Kluwer Academic Publishers, 79-119.

Hwang, K. B. and Zhang, B. T. (2005). An Introduction to Bayesian Networks: Concepts and Learning from Data, "", SNU Biointelligence Lab, 1-93.

Inouye, S. (1994). The dilemma of deliriun: Clinical and research controversies regarding diagnosis and evaluation of delirium in hospitalized elderly medical patients, The American Journal of Medicine, 97, 278-288. crossref(new window)

Inouye, S., Schlesinger, M. and Lyndon, T. (1999). Delirium: A symptom of how hospital care is failing older persons and a window to improve quality of hospital care, The American Journal of Medicine, 565-573.

Jensen, F. (1996). An Introduction to Bayesian Networks, Springer-verlag, New York.

Kwak, K., Lee, S. B. and Do, B. S. (2011). Delirium in an emergency department: A study of risk factors, Journal of the Korean Society of Emergency Medicine, Submitted.

Tan, P., Steinbach, M. and Kumar, V. (2007). Introduction to Data Mining, Addison Wesley Longman, California.

Warren, S. (1994). Neural networks and statistical models, Proceedings of the 19th Annual SAS Users Group International Conference, 1-13.