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stat.ME2026
Distinguishing case-mix from context heterogeneity in prognostic regression model synthesis settings
Max Behrens, Janis M. Nolde, Eleni Papakonstantinou +6
Prognostic regression models often synthesize data from multiple sites, whether within a multi-site study, across federated settings, or in individual participant data meta-analysi…
stat.ME2026
Contrasting Global and Patient-Specific Regression Models via a Neural Network Representation
Max Behrens, Daiana Stolz, Eleni Papakonstantinou +5
When developing clinical prediction models, it can be challenging to balance between global models that are valid for all patients and personalized models tailored to individuals o…
stat.ME2024
Improving prediction models by incorporating external data with weights based on similarity
Max Behrens, Maryam Farhadizadeh, Angelika Rohde +4
In clinical settings, we often face the challenge of building prediction models based on small observational data sets. For example, such a data set might be from a medical center…