What are the Challenges in Using Classification Algorithms for Cancer?
Despite their potential, classification algorithms face several challenges in cancer research:
Data Quality: Cancer datasets can be noisy, incomplete, or imbalanced, which can affect algorithm performance. Interpretability: Complex models, especially deep learning, often act as "black boxes," making it difficult for clinicians to understand the decision-making process. Generalizability: Models trained on specific datasets may not perform well on new data, limiting their applicability across different patient populations. Computational Resources: High-dimensional data, such as those from genomic studies, require significant computational power and storage.
