Abstract is missing.
- IDNetwork: A deep Illness-Death Network based on multi-states event history process for versatile disease prognosticationAziliz Cottin, Nicolas Pécuchet, Marine Zulian, Agathe Guilloux, Sandrine Katsahian. 1-21 [doi]
- Preface: AAAI Spring Symposium on Survival Prediction - Algorithms, Challenges, and Applications 2021Russell Greiner, Neeraj Kumar, Thomas Alexander Gerds, Mihaela van der Schaar. 1-2 [doi]
- Beta Survival ModelsDavid Hubbard, Benoit Rostykus, Yves Raimond, Tony Jebara. 22-39 [doi]
- Semi-Structured Deep Piecewise Exponential ModelsPhilipp Kopper, Sebastian Pölsterl, Christian Wachinger, Bernd Bischl, Andreas Bender 0001, David Rügamer. 40-53 [doi]
- WRSE - a non-parametric weighted-resolution ensemble for predicting individual survival distributions in the ICUJonathan Heitz, Joanna Ficek, Martin Faltys, Tobias M. Merz, Gunnar Rätsch, Matthias Hüser. 54-69 [doi]
- Improving the Calibration of Long Term Predictions of Heart Failure Rehospitalizations using Medical Concept EmbeddingSunil Vasu Kalmady, Weijie Sun, Justin Ezekowitz, Nowell Fine, Jonathan Howlett, Anamaria Savu, Russ Greiner, Padma Kaul. 70-82 [doi]
- Survival Trees for Current Status DataCe Yang, Liqun Diao, Richard Cook. 83-94 [doi]
- Wavelet Reconstruction Networks for Marked Point ProcessesJeremy Weiss. 95-106 [doi]
- The Safe Logrank Test: Error Control under Optional Stopping, Continuation and Prior MisspecificationPeter Grünwald, Alexander Ly, Muriel Perez-Ortiz, Judith Ter Schure. 107-117 [doi]
- Empirical Comparison of Continuous and Discrete-time Representations for Survival PredictionMichael Sloma, Fayeq Syed, Mohammedreza Nemati, Kevin S. Xu 0001. 118-131 [doi]
- Transformer-Based Deep Survival AnalysisShi Hu, Egill A. Fridgeirsson, Guido van Wingen, Max Welling. 132-148 [doi]
- Theory and software for boosted nonparametric hazard estimationDonald K. K. Lee, Ningyuan Chen, Hemant Ishwaran, Xiaochen Wang, Arash Pakbin, Bobak Mortazavi, Hongyu Zhao. 149-158 [doi]
- Dynamic Survival Analysis with Individualized Truncated Parametric DistributionsPreston Putzel, Padhraic Smyth, Jaehong Yu, Hua Zhong. 159-170 [doi]
- Harmonic-Mean Cox Models: A Ruler for Equal Attention to RiskXuejian Wang, Wenbin Zhang 0002, Aishwarya Jadhav, Jeremy C. Weiss. 171-183 [doi]
- Deep Parametric Time-to-Event Regression with Time-Varying CovariatesChirag Nagpal, Vincent Jeanselme, Artur Dubrawski. 184-193 [doi]
- Exploring the Wasserstein metric for time-to-event analysisTristan Sylvain, Margaux Luck, Joseph Paul Cohen, Héloïse Cardinal, Andrea Lodi 0001, Yoshua Bengio. 194-206 [doi]
- Survival Prediction Using Deep LearningAliasghar Tarkhan, Noah Simon, Thomas Bengtsson, Trung-Kien Nguyen, Jian Dai. 207-214 [doi]
- Risk and Survival Analysis from COVID Outbreak Data: Lessons from IndiaPrasad Bankar, Subhasis Panda, Vaibhav Anand, Vineet Kumar. 215-222 [doi]
- Deep-CR MTLR: a Multi-Modal Approach for Cancer Survival Prediction with Competing RisksSejin Kim, Michal Kazmierski, Benjamin Haibe-Kains. 223-231 [doi]
- Kullback-Leibler-Based Discrete Relative Risk Models for Integration of Published Prediction Models with New DatasetDi Wang, Wen Ye, Kevin He. 232-239 [doi]
- Finding Relevant Features for Different Times in Survival Prediction by Discrete Hazard Bayesian NetworkLi-Hao Kuan, Russell Greiner. 240-251 [doi]
- Multi-ethnic Survival Analysis: Transfer Learning with Cox Neural NetworksYan Gao, Yan Cui. 252-257 [doi]