POSTER SESSION B-10: Longitudinal Data Analysis
Tracks
POSTER AREA (M1 building upper floor)
| Wednesday, July 24, 2024 |
| 9:00 AM - 5:00 PM |
| POSTER AREA (M1 building upper floor) |
Presentations
Ms. Mélanie Guhl
Inserm, Paris, France
P-B10-01 | Semi-Bayesian methods to compute standard errors in nonlinear mixed effects models for sparse data
Dr. Markus Schepers
University of Mainz, Germany
P-B10-02 | Bayesian mixed models approach to exploring resilience dynamics: Impact of stress on subjective health and affects over time during the COVID-19 pandemic
Mr. Birzhan Akynkozhayev
Phd Student
Karolinska Institutet, Stockholm, Sweden
P-B10-03 | Longitudinal and joint models for PSA values and time to prostate cancer diagnosis
Ms. Yanjie Wang
Southern Medical University, Guangzhou , China
P-B10-04 | A dynamic prediction model for predicting the time to conversion to AD in patients with MCI Based on time-dependent covariates
Mr. Jamie Wong
PhD Student
University College London, United Kingdom
P-B10-05 | Emulating hypothetical physical activity interventions to assess obesity risk reduction: Applying target trial emulation in the 1958 British Birth Cohort
Dr. Denitsa Grigorova
Assistant Professor
Sofia University, Bulgaria
P-B10-06 | Modelling longitudinal cognitive test data with ceiling effects and left skewness
Ms. Sofia Kaisaridi
PhD student
Institut du Cerveau - Paris Brain Institute, France
P-B10-07 | A multivariate disease progression model for identifying subtypes in CADASIL
Ms. Maria De Martino
University of Udine, Italy
P-B10-08 | Use of interrupted time-series analysis to examine the progression of respiratory viruses amidst the SARS-CoV-2 pandemic
Ms. Juliette Ortholand
Inria, Paris Brain Institute, France
P-B10-09 | LEASPY: LEArning Spatiotemporal patterns in PYthon
Dr. Doug Thompson
Statistics Director
GlaxoSmithKline, Kilmacolm, United Kingdom
P-B10-10 | Design considerations for continuous time models in progressive diseases
Ms. Kiana Farhadyar
Faculty of Medicine and Medical Center, University of Freiburg, Germany
P-B10-11 | Impact of different longitudinal data representations on transformer performance in small data applications
Ms. Komal Aryal
PhD Candidate
McMaster University, Hamilton ON, Canada
P-B10-12 | Identifying factors associated with physician assistance in dying for older adults: A cohort study
Ms. Bashayr Aldawsari
Student
University of Liverpool, United Kingdom
P-B10-13 | Longitudinal clustering of liver cancer biomarkers
Prof. Francesca Little
University of Cape Town, South Africa
P-B10-14 | Examining heterogeneity in longitudinal data using latent class mixed effect modelling
Dr. Marta Spreafico
Leiden University, Netherlands
P-B10-15 | Cluster-based recurrent marked point process approach for longitudinal volume-outcome studies
Mr. Ottavio Khalifa
Inserm
P-B10-16 LB | Identifying clustering methods for longitudinal data with categorical features: A scoping review
