Fetching the paper…
Reading the bibliography…
We describe a new approach to estimating relative risks in time-to-event prediction problems with censored data in a fully parametric manner.
E. L. Kaplan and P. Meier, “Nonparametric estimation from incomplete observations,” Journal of the American statistical association
1958
Earlier work this paper cites.
D. R. Cox, “Regression models and life-tables,” Journal of the Royal Statistical Society: Series B (Methodological)
1972
Earlier work this paper cites.
F. E. Harrell, “Evaluating the yield of medical tests,” JAMA: The Journal of the American Medical Association
1982
Earlier work this paper cites.
D. Faraggi and R. Simon, “A neural network model for survival data,” Statistics in medicine
1995
Earlier work this paper cites.
W. A. Knaus, F. E. Harrell, J. Lynn, L. Goldman, R. S. Phillips, A. F. Connors, N. V. Dawson, W. J. Fulkerson, R. M. Califf, N. Desbiens, et al
1995
Earlier work this paper cites.
B. Schölkopf, A. Smola, and K.-R. Müller, “Kernel principal component analysis,” in International conference on artificial neural networks
1997
Earlier work this paper cites.
O. Rosen and M. Tanner, “Mixtures of proportional hazards regression models,” Statistics in Medicine
1999
Earlier work this paper cites.
J. P. Fine and R. J. Gray, “A proportional hazards model for the subdistribution of a competing risk,” Journal of the American statistical association
1999
Earlier work this paper cites.
E. Graf, C. Schmoor, W. Sauerbrei, and M. Schumacher, “Assessment and comparison of prognostic classification schemes for survival data,” Statistics in medicine
1999
Earlier work this paper cites.
A. Xiang, P. Lapuerta, A. Ryutov, J. Buckley, and S. Azen, “Comparison of the performance of neural network methods and cox regression for censored survival data,” Computational statistics & data analysis
2000
Earlier work this paper cites.
2001
Earlier work this paper cites.
C. Czado and F. Rudolph, “Application of survival analysis methods to long-term care insurance,” Insurance: Mathematics and Economics
2002
Earlier work this paper cites.
M. Stepanova and L. Thomas, “Survival analysis methods for personal loan data,” Operations Research
2002
Earlier work this paper cites.
John Wiley & Sons, 2002
A. M. Jones and O. O’Donnell, Econometric analysis of health data · 2002
Earlier work this paper cites.
L. Antolini, P. Boracchi, and E. Biganzoli, “A time-dependent discrimination index for survival data,” Statistics in Medicine
2005
Earlier work this paper cites.
J. Bosco Sabuhoro, B. Larue, and Y. Gervais, “Factors determining the success or failure of canadian establishments on foreign markets: A survival analysis approach,” The International Trade Journal
2006
Cited alongside, same era.
T. A. Gerds and M. Schumacher, “Consistent estimation of the expected brier score in general survival models with right-censored event times,” Biometrical Journal
2006
Cited alongside, same era.
A. Ghasemi, S. Yacout, and M. S. Ouali, “Optimal condition based maintenance with imperfect information and the proportional hazards model,” International Journal of Production Research
2007
Cited alongside, same era.
H. Ishwaran, U. B. Kogalur, E. H. Blackstone, M. S. Lauer, et al
2008
Cited alongside, same era.
C. Curtis, S. P. Shah, S.-F. Chin, G. Turashvili, O. M. Rueda, M. J. Dunning, D. Speed, A. G. Lynch, S. Samarajiwa, and Y. e. a. Yuan, “The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups,” Nature
J. Wang, C. Li, S. Han, S. Sarkar, and X. Zhou, “Predictive maintenance based on event-log analysis: A case study,” IBM Journal of Research and Development
2017
Later among the works it cites.
M. Mishra, J. Martinsson, M. Rantatalo, and K. Goebel, “Bayesian hierarchical model-based prognostics for lithium-ion batteries,” Reliability Engineering & System Safety
2017
Later among the works it cites.
A. M. Alaa and M. van der Schaar, “Deep multi-task gaussian processes for survival analysis with competing risks,” in Proceedings of the 31st International Conference on Neural Information Processing Systems
2017
Later among the works it cites.
J. Kraisangka and M. J. Druzdzel, “A bayesian network interpretation of the cox’s proportional hazard model,” Oct 2018
2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2012
Cited alongside, same era.
A. Hochstein, H.-I. Ahn, Y. T. Leung, and M. Denesuk, “Survival analysis for hdlss data with time dependent variables: Lessons from predictive maintenance at a mining service provider,” in Proceedings of 2013 IEEE International Conference on Service Operations and Logistics, and Informatics
2013
Cited alongside, same era.
B. Vinzamuri and C. K. Reddy, “Cox regression with correlation based regularization for electronic health records,” in 2013 IEEE 13th International Conference on Data Mining
2013
Cited alongside, same era.
T. A. Gerds, M. W. Kattan, M. Schumacher, and C. Yu, “Estimating a time-dependent concordance index for survival prediction models with covariate dependent censoring,” Statistics in Medicine
2013
Cited alongside, same era.
B. Vinzamuri, Y. Li, and C. K. Reddy, “Active learning based survival regression for censored data,” in Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management
2014
Cited alongside, same era.
M. Mirza and S. Osindero, “Conditional generative adversarial nets,” arXiv preprint arXiv:1411.1784
2014
Cited alongside, same era.
D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,” arXiv preprint arXiv:1412.6980
2014
Cited alongside, same era.
X. Zhu, J. Yao, and J. Huang, “Deep convolutional neural network for survival analysis with pathological images,” in 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
2016
Cited alongside, same era.
2018
Later among the works it cites.
P. Mobadersany, S. Yousefi, M. Amgad, D. A. Gutman, J. S. Barnholtz-Sloan, J. E. V. Vega, D. J. Brat, and L. A. Cooper, “Predicting cancer outcomes from histology and genomics using convolutional networks,” Proceedings of the National Academy of Sciences
2018
Later among the works it cites.
C. Lee, W. R. Zame, J. Yoon, and M. van der Schaar, “Deephit: A deep learning approach to survival analysis with competing risks,” in Thirty-Second AAAI Conference on Artificial Intelligence
2018
Later among the works it cites.
2018
Later among the works it cites.
D. W. Kim, S. Lee, S. Kwon, W. Nam, I.-H. Cha, and H. J. Kim, “Deep learning-based survival prediction of oral cancer patients,” Scientific reports
2019
Later among the works it cites.
2019
Later among the works it cites.
M. Z. Nezhad, N. Sadati, K. Yang, and D. Zhu, “A deep active survival analysis approach for precision treatment recommendations: Application of prostate cancer,” Expert Systems with Applications
2019
Later among the works it cites.
C. Lee, J. Yoon, and M. Van Der Schaar, “Dynamic-deephit: A deep learning approach for dynamic survival analysis with competing risks based on longitudinal data,” IEEE Transactions on Biomedical Engineering
2019
Later among the works it cites.
C. Lee, W. Zame, A. Alaa, and M. Schaar, “Temporal quilting for survival analysis,” in The 22nd International Conference on Artificial Intelligence and Statistics
2019
Later among the works it cites.
2019
Later among the works it cites.
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga, et al
2019
Later among the works it cites.