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Cited by in CrossRef
For: Caires Silveira E, Mattos Pretti S, Santos BA, Santos Corrêa CF, Madureira Silva L, Freire de Melo F. Prediction of hospital mortality in intensive care unit patients from clinical and laboratory data: A machine learning approach. World J Crit Care Med 2022; 11(5): 317-329 [PMID: 36160934 DOI: 10.5492/wjccm.v11.i5.317]
URL: https://www.wjgnet.com/2220-3141/full/v11/i5/317.htm
Number Citing Articles
1
Johayra Prithula, Muhammad E. H. Chowdhury, Muhammad Salman Khan, Khalid Al-Ansari, Susu M. Zughaier, Khandaker Reajul Islam, Abdulrahman Alqahtani. Improved pediatric ICU mortality prediction for respiratory diseases: machine learning and data subdivision insightsRespiratory Research 2024; 25(1) doi: 10.1186/s12931-024-02753-x
2
Zhenhua Song, Ke Ke. Prediction for CET-4 Based on Random ForestProcedia Computer Science 2023; 228: 429 doi: 10.1016/j.procs.2023.11.049
3
Sharmin Nahar Sharwardy, Hasan Sarwar, Mohammad Zahidur Rahman. Detection of anomalies in data of pediatric congenital heart disease ICU2023 26th International Conference on Computer and Information Technology (ICCIT) 2023; : 1 doi: 10.1109/ICCIT60459.2023.10441312
4
Baker Nawfal Jawad, Shakir Maytham Shaker, Izzet Altintas, Jesper Eugen-Olsen, Jan O. Nehlin, Ove Andersen, Thomas Kallemose. Development and validation of prognostic machine learning models for short- and long-term mortality among acutely admitted patients based on blood testsScientific Reports 2024; 14(1) doi: 10.1038/s41598-024-56638-6