Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Session Overview |
| Date: Wednesday, 19/Mar/2025 | |
| 8:00am - 9:00am |
Registration Location: Lobby |
| 9:00am - 9:15am |
Welcome Location: Wolfgang-Paul-Saal Chair: Alina Schenk Chair: Matthias Schmid |
| 9:15am - 10:15am |
Epidemiology Location: Wolfgang-Paul-Saal Chair: Benjamin Aretz Risk Prediction using Case-Cohort Samples: A Scoping Review and Empirical Comparison 9:35am - 9:55am Implication of the choice of time scales in survival analysis 9:55am - 10:15am Leveraging Cancer Incidence for Lead Time Estimation in Cancer Screening Programmes |
| 10:15am - 10:35am |
Coffee Break Location: Lobby |
| 10:35am - 11:35am |
Dynamic prediction models Location: Wolfgang-Paul-Saal Chair: Anders Munch Capturing subgroup-specific time-variation in covariate effects in Cox-type hazard regression models 10:55am - 11:15am Dynamic Prediction of Survival Benefit to Inform Liver Transplant Decisions in Hepatocellular Carcinoma 11:15am - 11:35am Dynamic prediction with numerous longitudinal predictors: how to combine the best of both worlds (landmarking and joint modelling) through penalized regression calibration |
| 11:35am - 11:45am |
Short Break Location: Lobby |
| 11:45am - 12:45pm |
Keynote I: Morten Overgaard Location: Wolfgang-Paul-Saal Chair: Alina Schenk Regression analysis with jack-knife pseudo-observations |
| 12:45pm - 1:45pm |
Lunch Break Location: Lobby |
| 1:45pm - 2:25pm |
Pseudo-observations Location: Wolfgang-Paul-Saal Chair: Alina Schenk Bootstrap-based inference for Pseudo-value regression models 2:05pm - 2:25pm Implications of Pseudo-Observations in Prognostic Modelling: Addressing Left Truncation. |
| 2:25pm - 6:00pm |
Mission AI Location: Deutsches Museum |
| 6:00pm - 8:00pm |
Poster Session Location: Schumpeter-Sitzungsraum Assurance methods for designing a clinical trial with a delayed treatment effect Investigating the most suitable modelling framework to predict long-term restricted mean survival time and life expectancy. Methods for Analyzing Multiple Time-to-Event Endpoints in Randomized Clinical Trials: A Comprehensive Overview Reconstructing Survival Curves: Using imputation Strategies to construct Kaplan-Meier Estimates with no or limited Data on Survivors A Pareto-Driven Ensemble Feature Selection Approach Optimizes Biomarker Discovery in Multi-omics Pancreatic Cancer Studies Increasing flexibility for the meta-analysis of full ROC curves – a copula approach Effective sample size for Cox models: A measure of individual uncertainty in survival predictions Imputation Free Deep Survival Prediction using Conditional Variational Autoencoders Building risk prediction models by synthesizing national registry and prevention trial data An R function for data preparation for an acyclic multistate model with non-ordered intermediate states. A Pragmatic Approach to the Estimation of the Interventional Absolute Risk in Continuous Time Testing the Similarity of Healthcare Pathways based on Transition Probabilities - A New Bootstrap Procedure Introducing a flexible model for regression models with a left-censored response and covariate. Extending landmarking to mixture cure models with time-varying covariates Multi-state models for individualized treatment response prediction and risk assessment in Multiple Myeloma Bayesian Joint Modeling of Bivariate Longitudinal and Time-to-Event Data: With Application of Micro and Macro Vascular Complication in People with Type 2 Diabetes and Hypertension. Does a SARS-CoV-2 infection increase the risk of dementia? An application of causal time-to-event analysis on real-world patient data Do commonly used Machine Learning implementations allow for IPCW to address censoring? A closer look at scikit-learn. Combining machine learning methods for subgroup identification in time-to-event data with approximate Bayesian computation for bias correction Planning early-phase clinical trials in oncology: A comprehensive simulation approach for Response, Progression-Free Survival, and Overall Survival CORALE project: Cumulative lifetime multi-exposures to ionising radiation and other risk factors and associations with chronic diseases in the CONSTANCES cohort Modeling the early-redemption of fixed interest rate mortgages: a survival analysis approach Bootstrapping LASSO-type estimators in Cox Frailty Models A Nonparametric Bayesian Approach for High-Dimensional Causal Effect Estimation in Survival Analysis Comparison of the Prognostic Performance of Machine Learning Algorithms on Gene Expression Data in Acute Myeloid Leukemia Double-truncated and censored corporate lifetimes: Likelihood and identification. Enhancing Healthcare Understanding from Clinical Routine Data by Simplifying the Representation of Treatment Pathways Improving Cox Regression Estimates by Using the Stochastic Approximation Expectation-Maximization Algorithm to Handle Missing Data Life expectancies and blood-based biomarkers for Alzheimer’s disease in primary care Propagator Methods for Survival Analysis Machine Learning for Survival Analysis: Predicting Time-to-Event Through Decomposition A Machine Learning Approach for Comparing Multiple Survival Curves: Random Forests with Reduced Assumption Dependency Principled estimation and prediction with competing risks: a Bayesian nonparametric approach Prediction Stability of Survival Models |
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