Clinical risk prediction models based on multicenter data: methods for model development and validation KU Leuven
Risk prediction models are developed to assist doctors in diagnosing patients, decision-making, counseling patients or providing a prognosis. To enhance the generalizability of risk models, researchers increasingly collect patient data in different settings and join forces in multicenter collaborations. The resulting datasets are clustered: patients from one center may have more similarities than patients from different centers, for example, ...