What Are the Challenges in Implementing Algorithms in Histology?
Implementing algorithms in histology poses several challenges. First, the quality of data is critical, as algorithms rely heavily on high-quality, annotated datasets to function optimally. Additionally, there is often a need for large amounts of labeled data to train models effectively, which can be resource-intensive. Another challenge lies in algorithm validation to ensure that the results are reliable and reproducible across different laboratories and settings.
