Back to the program

Contributed Papers

Advances in Statistical Learning and Computational Approaches in Survival Analysis

Thu, Aug 8, 10:30 AM - 12:20 PM

Mingzhao HuChair

Lifetime Data Science Section

6 Presentations

Mini-Batch Stochastic Gradient Descent for Cox Regression and Neural Network: Theoretical Foundation and Practice Guidance

10:35 AM - 10:50 AM

Lang Zeng (University of Pittsburgh)

Co-authors: Weijing Tang (Carnegie Mellon University), Ying Ding (University of Pittsburgh)

Comparison of correlated survival predictors: discriminatory accuracy evaluation using copula-based strategy

10:50 AM - 11:05 AM

Co-authors: Yongzhao Shao (New York University, School of Medicine)

Artificial neural networks for predicting clustered survival data

11:05 AM - 11:20 AM

Jing Wang (University of Utah)

Survival-based Clustering of Predictors in Cox Model with Application to TP53 Mutation Annotation

11:20 AM - 11:35 AM

Xiaoqian Liu (UT MD Anderson Cancer Center)

Co-authors: Haoming Shi (Rice University), Emilie Montellier (Université Grenoble Alpes), Pierre Hainaut (Université Grenoble Alpes), Wenyi Wang (MD Anderson Cancer Center)

Deep Learning for Regression Analysis of Interval-Censored Data

11:35 AM - 11:50 AM

Optimally tuned quantile random forests and random survival forests for estimating quantiles

11:50 AM - 12:05 PM

Matt Berkowitz (Simon Fraser University (SFU))

Co-authors: Thomas Loughin (Simon Fraser University), Rachel Altman (Simon Fraser University)

↑