Analysis shows enhanced interpretability in neurologic diseases clustering, suggesting new insights across methods.
Clustering complex biomedical data often produces multiple biologically plausible solutions. Retaining and comparing such solutions within a formal explanation space enhances interpretability and supports the discovery of complementary insights across methods.
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Yelugam et al. (2025) studied this question.
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