Structural instability in phenotype-oriented artificial intelligence: a conceptual perspective from a model system for primary care implementation.

Abstract excerpt

BACKGROUND: Artificial intelligence (AI) systems are increasingly deployed in primary care to classify complex, non-disease phenotypes such as frailty states, depression risk profiles, cardiometabolic subtypes, and multidimensional health constructs. While reported accuracy is often high, the structural stability of these systems across populations and practice environments remains insufficiently examined....

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