References
- Sun BC, Hsia RY, Weiss RE, et al. Effect of emergency department crowding on outcomes of admitted patients. Ann Emerg Med. 2013;61(6):605-611.
- Gaieski DF, Agarwal AK, Mikkelsen ME, et al. The impact of ED crowding on early interventions and mortality in patients with severe sepsis. Am J Emerg Med. 2017;35(7):953-960.
- Rathore SS, Curtis JP, Chen J, et al. National Cardiovascular Data Registry. Association of door-to-balloon time and mortality in patients admitted to hospital with ST elevation myocardial infarction: national cohort study. BMJ. 2009;338:b1807.
- Hautz WE, Kämmer JE, Hautz SC, et al. Diagnostic error increases mortality and length of hospital stay in patients presenting through the emergency room. Scand J Trauma Resusc Emerg Med. 2019;27(1):54.
- Feretzakis G, Loupelis E, Sakagianni A, et al. Using Machine Learning Techniques to Aid Empirical Antibiotic Therapy Decisions in the Intensive Care Unit of a General Hospital in Greece. Antibiotics (Basel). 2020;9(2):50.
- Raita Y, Goto T, Faridi MK, Brown DFM, Camargo CA Jr, Hasegawa K. Emergency department triage prediction of clinical outcomes using machine learning models. Crit Care. 2019;23(1):64.
- Yan L, Zhang HT, Goncalves J, et al. An interpretable mortality prediction model for COVID-19 patients. Nat Mach Intell. 2020;2:283-288.
- Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten I. The WEKA data mining software. ACM SIGKDD Explorations Newsletter. 2009;11(1):10–18.
- Kasperczuk A, Dardzinska A. Comparative Evaluation of the Different Data Mining Techniques Used for the Medical Database. Acta Mechanica Et Automatica. 2016;10(3):233– 238.
- Bouckaert R. Naive Bayes Classifiers That Perform Well with Continuous Variables. Lecture Notes in Computer Science. 2004;3339:1089-1094.
- Han J, Pei J, Yin Y. Mining frequent patterns without candidate generation, ACM SIGMOD International Conference on Management of Data. 2000;1–12.
- Rish, I. An empirical study of the naive bayes clas-sifier. InIJCAI workshop on Empirical Methods in AI. 2005
- John GH, Langley P: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.
- le Cessie S, van Houwelingen JC. Ridge Estimators in Logistic Regression. Applied Statistics. 1992;41(1):191-201.
- Freund Y, Schapire RE. Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
- Friedman J, Hastie T, Tibshirani R. Additive Logistic Regression: a Statistical View of Boosting. The Annals of Statistics. 2000;28(2):337-407.
- Frank E, Wang Y, Inglis S, Holmes G, Witten IH. Using model trees for classification. Machine Learning. 1998;32:63-76.
- Breiman L. Random Forests. Machine Learning. 2001;45:5-32.
- Breiman L. Bagging predictors. Machine Learning. 1996;24:123-140.
- Smith TC, Frank E. Introducing Machine Learning Concepts with WEKA. Methods Mol Biol. 2016;1418:353–378.
- Mandrekar JN. Receiver operating characteristic curve in diagnostic test assessment. J Thorac Oncol. 2010;5(9):1315-6.
- Fernandes M, Vieira SM, Leite F, Palos C, Finkelstein S, Sousa JMC. Clinical Decision Support Systems for Triage in the Emergency Department using Intelligent Systems: a Review. Artif Intell Med. 2020;102:101762.
- Levin S, Toerper M, Hamrock E, et al. Machine-Learning-Based Electronic Triage More Accurately Differentiates Patients With Respect to Clinical Outcomes Compared With the Emergency Severity Index. Ann Emerg Med. 2018;71(5):565-574.
- Weant KA, Bailey AM, Baker SN. Strategies for reducing medication errors in the emergency department. Open Access Emerg Med. 2014;6:45-55.
- Morley C, Unwin M, Peterson GM, Stankovich J, Kinsman L. Emergency department crowding: A systematic review of causes, consequences and solutions. PLoS One. 2018;13(8):e0203316.
- Reason J. Understanding adverse events: human factors. Qual Health Care. 1995;4(2):80-9.
- González J, Soltero R. Emergency Severity Index (ESI) triage algorithm: trends after implementation in the emergency department. Bol Asoc Med P R. 2009;101(3):7-10.