What Are the Challenges in Developing These Models?
Several challenges can arise in the development of risk prediction models:
Data Quality: Incomplete or inaccurate data can lead to biased models. Overfitting: Creating a model that performs well on the training data but poorly on new, unseen data. Generalizability: Ensuring the model is applicable to different populations beyond the one it was developed on.
