Matrix spillover remains a significant issue in flow cytometry analysis, influencing the accuracy of experimental results. Recently, machine learning algorithms have emerged as novel tools to mitigate matrix spillover effects. AI-mediated approaches leverage complex algorithms to detect spillover events and compensate for their impact on data in… Read More