What Challenges Exist in Implementing Machine Learning in Cancer Research?
Despite its potential, several challenges hinder the widespread adoption of ML in cancer research. One major issue is the quality and availability of data. Many datasets are small, biased, or lack comprehensive annotations, making it difficult to train accurate models. Additionally, the interpretability of ML models remains a concern, as clinicians need to understand the reasoning behind a model's predictions to trust and act upon them.
