Automation in clinical flow cytometry has the potential to revolutionize the field by improving processes and enhancing efficiency and accuracy. Integrating advanced robotics and artificial intelligence, these technologies can streamline sample preparation, data acquisition, and analysis. Automated sample handling reduces human error and increases throughput, allowing laboratories to handle larger volumes with consistent precision. Intelligent algorithms contribute to rapid data interpretation, aiding in the identification of cellular markers for disease diagnosis and monitoring. This automation not only accelerates turnaround times but also ensures reproducibility, making clinical flow cytometry a reliable tool in the realm of personalized medicine and diagnostics.
Keywords: Artificial intelligence; Automation; Flow cytometry; Sample handling; Throughput; Turnaround time.
Copyright © 2024 Elsevier Inc. All rights reserved.