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Article

Application of Machine Learning Methods in Nursing Home Research

1
College of Nursing, Keimyung University, 1095, Dalgubeol-daero, Dalseo-gu, Daegu 42601, Korea
2
Department of Management Information Systems, Jeju National University, Jeju-do 63243, Korea
3
College of Nursing, Ewha Womans University, Seoul 03760, Korea
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(17), 6234; https://doi.org/10.3390/ijerph17176234
Received: 5 August 2020 / Revised: 23 August 2020 / Accepted: 24 August 2020 / Published: 27 August 2020
Background: A machine learning (ML) system is able to construct algorithms to continue improving predictions and generate automated knowledge through data-driven predictors or decisions. Objective: The purpose of this study was to compare six ML methods (random forest (RF), logistics regression, linear support vector machine (SVM), polynomial SVM, radial SVM, and sigmoid SVM) of predicting falls in nursing homes (NHs). Methods: We applied three representative six-ML algorithms to the preprocessed dataset to develop a prediction model (N = 60). We used an accuracy measure to evaluate prediction models. Results: RF was the most accurate model (0.883), followed by the logistic regression model, SVM linear, and polynomial SVM (0.867). Conclusions: RF was a powerful algorithm to discern predictors of falls in NHs. For effective fall management, researchers should consider organizational characteristics as well as personal factors. Recommendations for Future Research: To confirm the superiority of ML in NH research, future studies are required to discern additional potential factors using newly introduced ML methods. View Full-Text
Keywords: machine learning; accidental falls; nursing homes machine learning; accidental falls; nursing homes
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MDPI and ACS Style

Lee, S.-K.; Ahn, J.; Shin, J.H.; Lee, J.Y. Application of Machine Learning Methods in Nursing Home Research. Int. J. Environ. Res. Public Health 2020, 17, 6234. https://doi.org/10.3390/ijerph17176234

AMA Style

Lee S-K, Ahn J, Shin JH, Lee JY. Application of Machine Learning Methods in Nursing Home Research. International Journal of Environmental Research and Public Health. 2020; 17(17):6234. https://doi.org/10.3390/ijerph17176234

Chicago/Turabian Style

Lee, Soo-Kyoung, Jinhyun Ahn, Juh H. Shin, and Ji Y. Lee 2020. "Application of Machine Learning Methods in Nursing Home Research" International Journal of Environmental Research and Public Health 17, no. 17: 6234. https://doi.org/10.3390/ijerph17176234

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