Conceptual framework demonstrates predictive risk detection in clinical laboratory workflows, suggesting earlier identification of specimen quality issues before downstream testing.
This paper proposes an AI Specimen Intelligence Platform, a conceptual framework for identifying specimen quality and processing risks early in laboratory workflows. The framework combines barcode validation, imaging, computer vision, predictive analytics, and operational decision support to help identify specimen concerns before downstream processing occurs. The paper discusses architecture, risk assessment models, operational workflows, implementation considerations, and future opportunities for predictive intelligence in laboratory operations.
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Maheswari Palle (2026) studied this question.
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