Matrix spillover remains a challenging issue in flow cytometry analysis, influencing the reliability of experimental results. Recently, deep neural networks have emerged as promising tools to mitigate matrix spillover effects. AI-mediated approaches leverage sophisticated algorithms to detect spillover events and adjust for their consequences on… Read More