Matrix spillover remains a challenging issue in flow cytometry analysis, influencing the reliability of experimental results. Recently, artificial intelligence (AI) have emerged as promising tools to mitigate matrix spillover effects. AI-mediated approaches leverage advanced algorithms to detect spillover events and compensate for their influence o