What are the Challenges in Predictive Modeling for Histology?
Despite its potential, predictive modeling in histology faces several challenges:
Data Quality: Ensuring high-quality, consistent data can be challenging. Feature Selection: Identifying the most relevant features for accurate predictions. Model Generalization: Ensuring the model performs well on new, unseen data. Interpretability: Making the model's predictions understandable for clinicians.
