Prediction of Sepsis Disease Using Random Search to Optimize Hyperparameter Tuning Based on Lazy Predict Model

Author:

Lydia E. Laxmi,Althubiti Sara A.,Anupama C. S. S.,Kumar Kollati Vijaya

Publisher

Springer Nature Singapore

Reference45 articles.

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2. Rhee, C., Dantes, R., Epstein, L., Murphy, D.J., Seymour, C.W., Iwashyna, T.J.: CDC Prevention Epicenter Program. Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009–2014. JAMA 318(13), 1241–1249, 03 Oct 2017. [FREE Full text] [https://doi.org/10.1001/jama.2017.13836] [Medline: 28903154]

3. Sakr, Y., Jaschinski, U., Wittebole, X., Szakmany, T., Lipman, J., Ñamendys-Silva, S.A.: ICON Investigators. Sepsis in intensive care unit patients: worldwide data from the intensive care over nations audit. Open Forum Infect. Dis. 5(12), ofy313 Dec 2018. [FREE Full text] [https://doi.org/10.1093/ofid/ofy313] [Medline: 30555852]

4. Rudd, K.E., Johnson, S.C., Agesa, K.M., Shackelford, K.A., Tsoi, D., Kievlan, D.R., et al.: Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the Global Burden of Disease Study. Lancet 395(10219), 200–211, 18 Jan 2020. [FREE Full text] [https://doi.org/10.1016/S0140-6736(19)32989-7] [Medline: 31954465]

5. Zhou, F., Yu, T., Du, R., Fan, G., Liu, Y., Liu, Z., et al.: Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 395(10229), 1054–1062, 28 Mar 2020. [https://doi.org/10.1016/S0140-6736(20)30566-3] [Medline: 32171076]

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