Abstract
Length of hospital stay (LOS) is closely related to the control of medical costs and the management of hospital resources. In this study, we implemented a data mining approach based on Back-Propagation (BP) neural net-works to construct a LOS prediction model that can help doctors and nurses individualize patient treatment. We analyzed medical data from 921 patients whowere diagnosed as cholecystitis and treated in a Chinese hospital between 2003and 2007. Our prediction model achieved approximately 80% accuracy, and revealed 5 LOS predictors: days before operation, wound grade, operation approach, charge type and number of admissions. The model can be easily used toprovide suggestions for doctors and nurses determining patient LOS.
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Li, JS., Tian, Y., Liu, YF., Shu, T., Liang, MH. (2013). Applying a BP Neural Network Model to Predict the Length of Hospital Stay. In: Huang, G., Liu, X., He, J., Klawonn, F., Yao, G. (eds) Health Information Science. HIS 2013. Lecture Notes in Computer Science, vol 7798. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37899-7_2
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DOI: https://doi.org/10.1007/978-3-642-37899-7_2
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