Matrix spillover remains a persistent issue in flow cytometry analysis, influencing the precision of experimental results. Recently, artificial intelligence (AI) have emerged as promising tools to mitigate matrix spillover effects. AI-mediated approaches leverage advanced algorithms to identify spillover events and correct for their consequences on