Comparison of the performance of neural network methods and Cox regression for censored survival data
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- Gaudart, Jean & Giusiano, Bernard & Huiart, Laetitia, 2004. "Comparison of the performance of multi-layer perceptron and linear regression for epidemiological data," Computational Statistics & Data Analysis, Elsevier, vol. 44(4), pages 547-570, January.
- Izquierdo, J. & Crespo Márquez, A. & Uribetxebarria, J., 2019. "Dynamic artificial neural network-based reliability considering operational context of assets," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 483-493.
- Li, Xingyu & Krivtsov, Vasiliy & Arora, Karunesh, 2022. "Attention-based deep survival model for time series data," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
- Kathrin Plankensteiner & Olivia Bluder & Jürgen Pilz, 2015. "Bayesian Network Model with Application to Smart Power Semiconductor Lifetime Data," Risk Analysis, John Wiley & Sons, vol. 35(9), pages 1623-1639, September.
- Lin Hao & Juncheol Kim & Sookhee Kwon & Il Do Ha, 2021. "Deep Learning-Based Survival Analysis for High-Dimensional Survival Data," Mathematics, MDPI, vol. 9(11), pages 1-18, May.
- Olivencia Polo, Fernando A. & Ferrero Bermejo, Jesús & Gómez Fernández, Juan F. & Crespo Márquez, Adolfo, 2015. "Failure mode prediction and energy forecasting of PV plants to assist dynamic maintenance tasks by ANN based models," Renewable Energy, Elsevier, vol. 81(C), pages 227-238.
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