Matrix spillover remains a significant issue in flow cytometry analysis, influencing the accuracy of experimental results. Recently, artificial intelligence (AI) have emerged as promising tools to mitigate matrix spillover effects. AI-mediated approaches leverage complex algorithms to detect spillover events and adjust for their influence on data i