Matrix spillover remains a persistent issue in flow cytometry analysis, influencing the reliability of experimental results. Recently, artificial intelligence (AI) have emerged as novel tools to mitigate matrix spillover effects. AI-mediated approaches leverage sophisticated algorithms to quantify spillover events and adjust for their influence on