Interpretation of cluster structures in pain-related phenotype data using explainable artificial intelligence (XAI).

Abstract excerpt

BACKGROUND: In pain research and clinics, it is common practice to subgroup subjects according to shared pain characteristics. This is often achieved by computer-aided clustering. In response to a recent EU recommendation that computer-aided decision making should be transparent, we propose an approach that uses machine learning to provide (1) an understandable interpretation of a cluster structure to (2) enable...

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