Wake Forest University, 1 Medical Center Boulevard, Winston-Salem, NC 27157, USA.
Flow Cytometry Laboratory, University of Louisville Health, 529 S Jackson Street, Louisville, KY 40202, USA.
Clin Lab Med. 2024 Sep;44(3):455-463. doi: 10.1016/j.cll.2024.04.007. Epub 2024 May 30.
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.
临床流式细胞术的自动化有潜力通过改进流程、提高效率和准确性来彻底改变这个领域。通过整合先进的机器人技术和人工智能，这些技术可以简化样本制备、数据采集和分析。自动化的样本处理减少了人为错误并提高了通量，使实验室能够以一致的精度处理更大的样本量。智能算法有助于快速的数据解释，有助于识别用于疾病诊断和监测的细胞标志物。这种自动化不仅加速了周转时间，而且还确保了可重复性，使临床流式细胞术成为个性化医疗和诊断领域的可靠工具。
