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[1] Frank E. Harrell,et al. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2001 .
[2] John B. Willett,et al. It’s About Time: Using Discrete-Time Survival Analysis to Study Duration and the Timing of Events , 1993 .
[3] Li Li,et al. Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records , 2016, Scientific Reports.
[4] William Moran,et al. On the use of artificial neural networks for the analysis of survival data , 1997, IEEE Trans. Neural Networks.
[5] I. Graham,et al. Value and limitations of existing scores for the assessment of cardiovascular risk: a review for clinicians. , 2009, Journal of the American College of Cardiology.
[6] N. Breslow,et al. A Large Sample Study of the Life Table and Product Limit Estimates Under Random Censorship , 1974 .
[7] Albee Y. Ling,et al. A Clinical Score for Predicting Atrial Fibrillation in Patients with Cryptogenic Stroke or Transient Ischemic Attack , 2017, Cardiology.
[8] T. Panzarella,et al. Accuracy of survival prediction by palliative radiation oncologists. , 2005, International journal of radiation oncology, biology, physics.
[9] D Faraggi,et al. A neural network model for survival data. , 1995, Statistics in medicine.
[10] Uri Shaham,et al. DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network , 2016, BMC Medical Research Methodology.
[11] Travers Ching,et al. Cox-nnet: an artificial neural network Cox regression for prognosis prediction , 2016 .
[12] D.,et al. Regression Models and Life-Tables , 2022 .
[13] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[14] H. Prigerson,et al. Clinical trial participation as part of end-of-life cancer care: associations with medical care and quality of life near death. , 2014, Journal of pain and symptom management.
[15] R. Kay. The Analysis of Survival Data , 2012 .
[16] James E. Helmreich. Regression Modeling Strategies with Applications to Linear Models, Logistic and Ordinal Regression and Survival Analysis (2nd Edition) , 2016 .
[17] P. Royston,et al. Flexible parametric proportional‐hazards and proportional‐odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects , 2002, Statistics in medicine.
[18] Egil Martinsson,et al. WTTE-RNN : Weibull Time To Event Recurrent Neural Network A model for sequential prediction of time-to-event in the case of discrete or continuous censored data, recurrent events or time-varying covariates , 2017 .
[19] Jeffrey Dean,et al. Scalable and accurate deep learning with electronic health records , 2018, npj Digital Medicine.
[20] U. G. Dailey. Cancer,Facts and Figures about. , 2022, Journal of the National Medical Association.
[21] Andrew Y. Ng,et al. Improving palliative care with deep learning , 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
[22] Xun Zhu,et al. Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data , 2018, PLoS Comput. Biol..
[23] P. Royston,et al. External validation of a Cox prognostic model: principles and methods , 2013, BMC Medical Research Methodology.
[24] Daniel L. Rubin,et al. Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) Utilizing Free-Text Clinical Narratives , 2018, Scientific Reports.
[25] Christopher H Jackson,et al. flexsurv: A Platform for Parametric Survival Modeling in R. , 2016, Journal of statistical software.
[26] E. Emanuel,et al. Comparison of Site of Death, Health Care Utilization, and Hospital Expenditures for Patients Dying With Cancer in 7 Developed Countries. , 2016, JAMA.