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Contributed Papers

Machine Learning and Predictive Methods for Survival Data

Sun, Aug 2, 2:00 PM - 3:50 PM Room CC-105 Thomas M. Menino Convention & Exhibition Center

Tiange ZhengChair

Lifetime Data Science Section

7 Presentations

Federated Survival Analysis with Site-Level Heterogeneity Adjustment

2:05 PM - 2:20 PM

Hyojung Jang (Northwestern University)

Co-authors: Malcolm Risk, Yaojie Wang (Northwestern University Feinberg School of Medicine), Norrina Allen (Northwestern University), Xu Shi, Lili Zhao (Northwestern University)

Federated Learning Survival Analysis Heterogeneity across sites Privacy-preserting Multi-site network

High Dimensional Inference via Regularized Extended Fiducial Inference in Survival Analysis

2:20 PM - 2:35 PM

Co-authors: Teng Fei (Memorial Sloan Kettering Cancer Center)

Markov chain Monte Carlo Feature selection Confidence interval Uncertainty quantification Deep neural network Cox regression

Improving the within-node estimation of survival trees while retaining interpretability

2:35 PM - 2:50 PM

Co-authors: Haolin Li (Boston University), Jianwen Cai (University of North Carolina at Chapel Hill)

Survival Analysis Censored Data Decision Tree Interpretable Machine Learning Nonparametric Statistics

Novel subgroup identification method through win probability for RCTs with survival endpoints

2:50 PM - 3:05 PM

Na Bo (Virgnia Commonwealth University)

Co-authors: Ying Ding (University of Pittsburgh)

heterogeneous treatment effect precision medicine randomized clinical trials simultaneous inference subgroup identification win probability

Smooth Concordance Metrics for Survival Models

3:05 PM - 3:20 PM

Nicholas Hartman

Co-authors: Grace Richards (University of Michigan)

Hazard Function Predictive Modeling Receiver Operating Characteristic Curve Time-to-Event Data

Stah and stahreg: Stata commands for survival analysis using the average hazard with survival weight

3:20 PM - 3:35 PM

Co-authors: Hajime Uno (Dana-Farber Cancer Institute)

average hazard survival weight restricted mean survival time model-free survival analysis stratified analysis

A Unified Rank-Based Decision Framework for Personalized Treatment Selection with Mixed-Type Outcome

3:35 PM - 3:50 PM

Chathura Siriwardhana (University of Hawaii)

Co-authors: K.B. Kulasekera (University of Louisville), Bakeerathan Gunaratnam (University of Louisville)

Personalized Treatments Multivariate outcomes Mixed outcome types Rank-based methods Ensemble methods

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