unsupervised learning

What are the Challenges of Using Unsupervised Learning in Cancer Research?

One of the main challenges is the high dimensionality and complexity of biological data. Cancer datasets often contain thousands of genes and other molecular features, making it difficult to identify meaningful patterns. Additionally, the heterogeneity of cancer means that tumors of the same type can vary significantly between patients. Finally, the interpretability of unsupervised learning models can be challenging, requiring domain expertise to make sense of the results.

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