Education for Statistics in Practice: Development and evaluation of prediction models: pitfalls and solutions
Ben Van Calster1, Marten van Smeden2
1Department of Development and Regeneration, University of Leuven, Leuven, Belgium; 2Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
With fast developments in medical statistics, machine learning and artificial intelligence, the current opportunities for making accurate predictions about the future seem nearly endless. In this lecture we will share some experiences from a medical prediction perspective, where prediction modelling has a long history and models have been implemented in patient care with varying success. We will focus on best practices for the development, evaluation and presentation of prediction models, highlight some common pitfalls, present solutions to circumvent bad prediction modelling and discuss some methodological challenges for the future.