" From Data to Decisions: Critical Considerations in Clinical Prediction Modelling"
Fantastic turn out for today's cross-IAHS Methodological Innovation seminar.
David McLernon from the Biostatistics and Health Data Science group presented a deep dive on the methods of Clinical Prediction Modelling.
Clinical prediction models are algorithms developed using statistical modelling or machine learning that combines patient characteristics to predict a diagnostic or prognostic outcome. They can be used to inform patients of their risk of some health outcome or to support clinical decisions around referral or treatment. It is important that models are developed and assessed appropriately to ensure predictions are accurate and do not lead to harmful decision-making. David focused on some of the critical issues to consider before, during and after model development that are often ignored or addressed poorly.
Keep a look out for further seminars in this series organised through the cross-IAHS Methodological Innovation Group.
Please contact iahsadmin@abdn.ac.uk if you would like more information.