What Are the Challenges in Improving Model Performance?
Several challenges can impede the improvement of model performance:
1. Data Limitations: Incomplete or inaccurate data can lead to unreliable models. Issues like underreporting, missing data, and biases can significantly affect model accuracy.
2. Complexity of Diseases: The multifactorial nature of diseases, especially those with unknown transmission dynamics, makes modeling challenging.
3. Computational Constraints: Advanced models often require significant computational resources, which may not be readily available in all settings.
4. Ethical Concerns: Ensuring the privacy and security of health data is paramount. Balancing data utility and ethical considerations can be challenging.
