What are the Challenges in Implementing Computational Methods in Histology?
Despite the benefits, there are several challenges in integrating computational power into histology:
Data Quality: High-quality, annotated datasets are required to train machine learning models effectively. Interpretability: Ensuring that the results generated by computational methods are interpretable and actionable for pathologists. Technical Expertise: The need for interdisciplinary knowledge combining histology, computer science, and bioinformatics. Computational Resources: High-performance computing resources are often necessary to process large histological datasets.
