Survival analysisDeep Learning
DeepSurv
DeepSurv是一种深度神经网络方法，用于生存分析，可以直接从数据中学习个性化的生存分布。Katzman等人于2018年提出，它通过使用深度学习来捕捉协变量与生存结果之间复杂的非线性关系，从而扩展了Cox比例风险模型。它解决了在高维环境中建模异质治疗效果和事件发生时间预测的问题。
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来源
- Faraggi, D., & Simon, R. (1995). A neural network model for survival data. Statistics in Medicine, 14(1), 73–82. DOI: 10.1002/sim.4780140108 ↗
- Katzman, J. L., et al. (2018). DeepSurv: Personalized treatment recommender system using a Cox proportional hazards deep neural network. Journal of Machine Learning Research, 40, 40–51. DOI: 10.1186/s12874-018-0482-1 ↗
- Lee, C., Zame, W., Yoon, J., & van der Schaar, M. (2018). Deephit: A deep learning approach for dynamic survival analysis. AAAI Conference on Artificial Intelligence, 32(1). link ↗
如何引用本页
ScholarGate. (2026, June 3). Deep Learning for Survival Analysis. ScholarGate. https://scholargate.app/zh/survival/deepsurv
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