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There is currently great interest in applying neural networks to prediction tasks in medicine.
Regression models and life-tables
Cox, D. (1972) · 1972
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Covariance analysis of censored survival data
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A large sample study of the life table and product limit estimates under random censorship
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Stochastic gradient learning in neural networks
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The SUPPORT prognostic model. Objective estimates of survival for seriously ill hospitalized adults. Study to understand prognoses and preferences for outcomes and risks of treatments
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On the use of artificial neural networks for the analysis of survival data
Brown, S. F., Branford, A. J., and Moran, W. (1997) · 1997
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Gradient-based learning applied to document recognition
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Assessment and comparison of prognostic classification schemes for survival data
Graf, E., Schmoor, C., Sauerbrei, W., and Schumacher, M. (1999) · 1999
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Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects
Royston, P. and Parmar, M. K. (2002) · 2002
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Value and limitations of existing scores for the assessment of cardiovascular risk: a review for clinicians
Cooney, M. T., Dudina, A. L., and Graham, I. M. (2009) · 2009
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Wtte-rnn: Weibull time to event recurrent neural network
Martinsson, E. (2016) · 2016
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Deep patient: An unsupervised representation to predict the future of patients from the electronic health records
Miotto, R., Li, L., Kidd, B. A., and Dudley, J. T. (2016) · 2016
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Improving palliative care with deep learning
Avati, A., Jung, K., Harman, S., Downing, L., Ng, A., and Shah, N. H. (2017) · 2017
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A clinical score for predicting atrial fibrillation in patients with cryptogenic stroke or transient ischemic attack
Kwong, C., Ling, A. Y., Crawford, M. H., Zhao, S. X., and Shah, N. H. (2017) · 2017
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Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data
Ching, T., Zhu, X., and Garmire, L. X. (2018) · 2018
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External validation of a cox prognostic model: principles and methods
Royston, P. and Altman, D. G. (2013) · 2013
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Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis (Springer Series in Statistics)
Harrell Jr., F. E. (2015) · 2015
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flexsurv: a platform for parametric survival modelling in r
Jackson, C. H. (2016) · 2016
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DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network
Katzman, J. L., Shaham, U., Cloninger, A., Bates, J., Jiang, T., and Kluger, Y. (2018) · 2018
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Scalable and accurate deep learning with electronic health records
Rajkomar, A., Oren, E., Chen, K., Dai, A. M., Hajaj, N., Hardt, M., Liu, P. J., Liu, X., Marcus, J., Sun, M., et al. (2018) · 2018
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Lecture notes for wws 509: Generalized linear statistical models, princeton university
Rodriguez, G. (2016) · 2018
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