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Comparison of the performance of neural network methods and Cox regression for censored survival data

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  • Xiang, Anny
  • Lapuerta, Pablo
  • Ryutov, Alex
  • Buckley, Jonathan
  • Azen, Stanley

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Suggested Citation

  • Xiang, Anny & Lapuerta, Pablo & Ryutov, Alex & Buckley, Jonathan & Azen, Stanley, 2000. "Comparison of the performance of neural network methods and Cox regression for censored survival data," Computational Statistics & Data Analysis, Elsevier, vol. 34(2), pages 243-257, August.
    • Handle: RePEc:eee:csdana:v:34:y:2000:i:2:p:243-257
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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).
    5. 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.
    6. 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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