Recent advancements in risk prediction models are driven by several factors:
1. Big Data: The availability of large datasets from electronic health records, genomic studies, and social determinants of health. 2. Machine Learning: The application of machine learning algorithms to identify complex patterns and interactions among risk factors. 3. Genomic Data: Integration of genomic information to predict the risk of hereditary diseases. 4. Wearable Technology: Real-time data from wearable devices that monitor physiological parameters.
