摘要
一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-人工智能的新研究是一篇报道的主题。根据NewsRx记者从中国北京发回的新闻报道，研究表明：“基于患者的实时QC(PBRTQC)使用来自患者的数据来评估分析性能。PBR TQC算法与计算机科学的发展和更强大的计算机的可用性同步发展。”我们的新闻记者从中国科学院大学的研究中获得了一句话：“人工智能在PBRTQC中的应用很快，与传统方法相比有许多明显的优势。然而，直到本文综述之前，还没有对这些方法进行批判性的比较。本文描述和对比了基于移动平均法、回归调整实时QC、神经网络和异常检测的PBRTQC算法。”
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news originating from Beijing, People 's Republic of China, by NewsRx correspondents, research stated, "Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBR TQC algorithms have advanced in parallel with developments in computer science a nd the increased availability of more powerful computers." Our news journalists obtained a quote from the research from the University of t he Chinese Academy of Sciences, "The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. Howev er, until this review, there has been no critical comparison of these. The PBRTQ C algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted."
NETL
NSTL