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A multicenter cross-sectional study reveals machine learning can effectively predict nursing interruptions in medication administration, suggesting improved management.
This study systematically evaluated multiple influencing factors of NIMA and developed three internally validated risk prediction models of NIMA. The LR-based nomogram and the web-based calculators showed the most consistent performance and may support risk stratification and targeted nursing management, pending external validation and feasibility assessment.
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Dong et al. (2026) studied this question.
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