Kim, K.S.; Yoon, T.J.; Ahn, J.; Ryu, J.-A.
Development and Validation of a Machine Learning Model for Early Prediction of Acute Kidney Injury in Neurocritical Care: A Comparative Analysis of XGBoost, GBM, and Random Forest Algorithms. Diagnostics 2025, 15, 2061.
https://doi.org/10.3390/diagnostics15162061
AMA Style
Kim KS, Yoon TJ, Ahn J, Ryu J-A.
Development and Validation of a Machine Learning Model for Early Prediction of Acute Kidney Injury in Neurocritical Care: A Comparative Analysis of XGBoost, GBM, and Random Forest Algorithms. Diagnostics. 2025; 15(16):2061.
https://doi.org/10.3390/diagnostics15162061
Chicago/Turabian Style
Kim, Keun Soo, Tae Jin Yoon, Joonghyun Ahn, and Jeong-Am Ryu.
2025. "Development and Validation of a Machine Learning Model for Early Prediction of Acute Kidney Injury in Neurocritical Care: A Comparative Analysis of XGBoost, GBM, and Random Forest Algorithms" Diagnostics 15, no. 16: 2061.
https://doi.org/10.3390/diagnostics15162061
APA Style
Kim, K. S., Yoon, T. J., Ahn, J., & Ryu, J.-A.
(2025). Development and Validation of a Machine Learning Model for Early Prediction of Acute Kidney Injury in Neurocritical Care: A Comparative Analysis of XGBoost, GBM, and Random Forest Algorithms. Diagnostics, 15(16), 2061.
https://doi.org/10.3390/diagnostics15162061