Identification of <scp>IV</scp> fluid contamination in complete blood counts and subsequent unnecessary red blood cell transfusions using artificial intelligence

The findings support the feasibility of using ML to identify IV fluid contamination in CBC results efficiently and effectively. Further work, including prospective real-world evaluations, targeted quality improvement initiatives, and development of real-time detection models, is necessary before realizing the potential benefits to patient safety, laboratory operations, and patient blood management.