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- پیش بینی مدت اقامت بیماران در بخش مراقبت های ویژه مغز و اعصاب با تکنیک های داده کاوی
پیش بینی مدت اقامت بیماران در بخش مراقبت های ویژه مغز و اعصاب با تکنیک های داده کاوی
Prediction of the length of stay of patients in the neuro-critical care unit using
data mining techniques
چکیده
موضوع:
تمام متن:
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مراجع
Awad A, Bader–El–Den M, McNicholas J. Patient length of stay and mortality prediction: A survey. Health Services Management Research. 2017:0951484817696212.
World-Bank. World Bank 2017. Available from: https://data.worldbank.org/indicator/SH.XPD.TOTL.ZS.
WHO. Wolrd Health Organization 2017. Available from: http://www.who.int/gho/health_financing/total_expenditure/en/.
Awad A, Bader-El-Den M, McNicholas J. Modeling and Predicting Patient Length of Stay: A Survey. 2016.
Veloso R, Portela F, Santos M, Machado JM, Abelha A, Silva Á, et al., editors. Real-time data mining models for predicting length of stay in intensive care units. KMIS 2014-International Conference on Knowledge Management and Information Sharing; 2014.
Seemab S, Qamar U. PEDICTING PATIENT’S LENGTH OF STAY BY MINING HOSPITAL DATA. 2015.
Hunter A, Johnson L, Coustasse A. Reduction of intensive care unit length of stay: the case of early mobilization. The health care manager. 2014;33(2):128-35.
Kramer AA, Zimmerman JE. A predictive model for the early identification of patients at risk for a prolonged intensive care unit length of stay. BMC medical informatics and decision making. 2010;10(1):27.
Xiao J, Douglas D, Lee AH, Vemuri SR. A Delphi evaluation of the factors influencing length of stay in Australian hospitals. The International journal of health planning and management. 1997;12(3):207-18.
Ravangard R, Arab M, Zeraati H, Rashidian A, Akbarisari A, Niroomand N, et al. A STUDY OF PATIENT LENGTH OF STAY IN TEHRAN UNIVERSITY OF MEDICAL SCIENCES’OBSTETRICS AND GYNECOLOGY SPECIALTY HOSPITAL AND ITS ASSOCIATED CLINICAL AND NONCLINICAL FACTORS. 2010.
Azari A, Janeja VP, Mohseni A, editors. Predicting hospital length of stay (phlos): A multi-tiered data mining approach. Data Mining Workshops (ICDMW), 2012 IEEE 12th International Conference on; 2012: IEEE.
Khajehali N, Alizadeh S. Extract critical factors affecting the length of hospital stay of pneumonia patient by data mining (case study: an Iranian hospital). Artificial Intelligence in Medicine. 2017.
Hachesu PR, Ahmadi M, Alizadeh S, Sadoughi F. Use of data mining techniques to determine and predict length of stay of cardiac patients. Healthcare informatics research. 2013;19(2):121-9.
Guiza Grandas F, Fierens D, Ramon J, Blockeel H, Meyfroidt G, Bruynooghe M, et al., editors. Predictive data mining in intensive care. Proceedings of the 15th Annual Machine Learning Conference of Belgium and The Netherlands (BENELEARN); 2006.
Navaz AN, Mohammed E, Serhani MA, Zaki N, editors. The use of data mining techniques to predict mortality and length of stay in an ICU. Innovations in Information Technology (IIT), 2016 12th International Conference on; 2016: IEEE.
Kim S, Kim W, Park RW. A comparison of intensive care unit mortality prediction models through the use of data mining techniques. Healthcare informatics research. 2011;17(4):232-43.
Friedman JH, Kohavi R, Yun Y, editors. Lazy decision trees. AAAI/IAAI, Vol 1; 1996.
Rokach L, Maimon O. Data mining with decision trees: theory and applications: World Scientific; 2008.
Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, Motoda H, et al. Top 10 algorithms in data mining. Knowledge and information systems. 2008;14(1):1-37.
Chou S-M, Lee T-S, Shao YE, Chen I-F. Mining the breast cancer pattern using artificial neural networks and multivariate adaptive regression splines. Expert Systems with Applications. 2004;27(1):133-42.
Akar Ö, Güngör O. Classification of multispectral images using Random Forest algorithm. Journal of Geodesy and Geoinformation. 2013;1(2).
Huang JQ, Hooper PM, Marrie TJ. Factors associated with length of stay in hospital for suspected community-acquired pneumonia. Canadian respiratory journal. 2006;13(6):317-24.
Hastie T, Tibshirani R, Friedman J. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Biometrics. 2002.
Tu JV, Guerriere MR. Use of a neural network as a predictive instrument for length of stay in the intensive care unit following cardiac surgery. Computers and biomedical research. 1993;26(3):220-9.
Sheikh-Nia S. An Investigation of Standard and Ensemble Based Classification Techniques for the Prediction of Hospitalization Duration 2012.
Zheng B, Zhang J, Yoon SW, Lam SS, Khasawneh M, Poranki S. Predictive modeling of hospital readmissions using metaheuristics and data mining. Expert Systems with Applications. 2015;42(20):7110-20.
Jiang X, Qu X, Davis LB, editors. Using Data Mining to Analyze Patient Discharge Data for an Urban Hospital. DMIN; 2010.
Mohammadebrahimi S, Bayati S, Mardani M, Karim H. Factors Associated with Patient Length of Stay, According to Sina Hospital’s Admission Data-Mashhad. Iranian Journal of Medical Informatics. 2015;4(4).
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