Prospective and External Validation of an Ensemble Learning Approach to Sensitively Detect Intravenous Fluid Contamination in Basic Metabolic Panels
Spies N, Militello L, Farnsworth C, El-Khoury J, Durant T, Zaydman M. Prospective and External Validation of an Ensemble Learning Approach to Sensitively Detect Intravenous Fluid Contamination in Basic Metabolic Panels. Clinical Chemistry 2024, 71: 296-306. PMID: 39545815, DOI: 10.1093/clinchem/hvae168.Peer-Reviewed Original ResearchSHapley Additive exPlanationsLearning approachDetection of contamination eventsUnsupervised learning approachLearning-based methodsMachine learning-based methodsEnsemble learning approachMachine learning pipelineEnsemble learningLearning pipelineMatthews correlation coefficientAlgorithmic fairnessReal worldSHapley Additive exPlanations valuesCurrent workflowsClinical workflowWorkflowOperational burdenBasic metabolic panelIntravenous (IVPipelineInternal validation setValidation setFlagging ratesPerformance assessment
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