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| Use of Data Mining Techniques to Determine and Predict Length of Stay of Cardiac Patients |
| Peyman Rezaei Hachesu, Maryam Ahmadi, Somayyeh Alizadeh, Farahnaz Sadoughi |
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Healthc Inform Res. 2013;19(2):121-129. Published online June 30, 2013 DOI: https://doi.org/10.4258/hir.2013.19.2.121 |
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Use of Data Mining Techniques to Determine and Predict Length of Stay of Cardiac Patients Healthcare Informatics Research. 2013;19(2):121  A Machine Learning Approach to Predict Length of Stay for Opioid Overdose Admitted Patients 2021 IEEE International Conference on Big Data (Big Data). 2021; Predicting Hospital Length of Stay of Neonates Admitted to the NICU Using Data Mining Techniques 2020 10th International Conference on Computer and Knowledge Engineering (ICCKE). 2020; NT-proBNP Does Not Predict the Length of Hospital Stay in Patients Admitted with Systolic Heart Failure Exacerbation Journal of Cardiac Failure. 2009;15(6):S35-S36 Predefined and data driven CT densitometric features predict critical illness and hospital length of stay in COVID-19 patients . 2021; Why do ‘fast track’ patients stay more than four hours in the emergency department? An investigation of factors that predict length of stay Emergency Medicine Australasia. 2018;30(5):641-647 Can undernutrition predict length of stay in patients admitted to a short-stay acute care unit? Proceedings of the Nutrition Society. 2009;68(OCE1): The Use of Data Mining Techniques to Predict Employee Performance: A Literature Review 2023 International Conference On Cyber Management And Engineering (CyMaEn). 2023; Predefined and data driven CT densitometric features predict critical illness and hospital length of stay in COVID-19 patients Scientific Reports. 2022;12(1): The Use of an Accelerated Diagnostic Protocol and a Chest Pain Unit Reduces Length of Stay in Patients with Non-Cardiac Chest Pain Heart, Lung and Circulation. 2017;26:S15 |
