自动化
周转时间
计算机科学
样品(材料)
人工智能
实验室自动化
吞吐量
机器人学
领域(数学)
鉴定(生物学)
数据采集
工程类
机器人
生物
机械工程
电信
化学
植物
数学
色谱法
纯数学
无线
操作系统
作者
Giovanni Insuasti‐Beltran,Ahmad Al‐Attar
标识
DOI:10.1016/j.cll.2024.04.007
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI