Detection of Falsely Elevated Point-of-Care Potassium Results Due to Hemolysis Using Predictive Analytics.
Journal:
American journal of clinical pathology
PMID:
32367140
Abstract
OBJECTIVES: Preanalytical factors, such as hemolysis, affect many components of a test panel. Machine learning can be used to recognize these patterns, alerting clinicians and laboratories to potentially erroneous results. In particular, machine learning might identify which cases of elevated potassium from a point-of-care (POC) basic metabolic panel are likely erroneous.