Application of Patient-Based Real-Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening.

Journal: Journal of clinical laboratory analysis
PMID: 38468408

Abstract

BACKGROUND: Patient-based real-time quality control (PBRTQC) has gained attention because of its potential to continuously monitor the analytical quality in situations wherein internal quality control (IQC) is less effective. Therefore, we tried to investigate the application of PBRTQC method based on an artificial intelligence monitoring (AI-MA) platform in quality risk monitoring of Down syndrome (DS) serum screening.

Authors

  • Xuran Yang
    Department of Clinical Medicine Laboratory, Xiaolan People's Hospital of Zhongshan, Zhongshan, Guangdong, China.
  • Qianlan Chen
    School of Economics and Management, Guangxi Normal University, Guilin, China.
  • Zhifeng Pan
    Department of Clinical Medicine Laboratory, Xiaolan People's Hospital of Zhongshan, Zhongshan, Guangdong, China.
  • Jingmao Cheng
    Department of Clinical Medicine Laboratory, Xiaolan People's Hospital of Zhongshan, Zhongshan, Guangdong, China.
  • Wenting Zheng
    Department of Clinical Medicine Laboratory, Xiaolan People's Hospital of Zhongshan, Zhongshan, Guangdong, China.
  • Yingliang Liang
    Department of Clinical Medicine Laboratory, Xiaolan People's Hospital of Zhongshan, Zhongshan, Guangdong, China.
  • Hui Chen
    Xiangyang Central HospitalAffiliated Hospital of Hubei University of Arts and Science Xiangyang 441000 China.
  • Guanghui Chen
    Department of Orthopedics, Peking University Third Hospital, Beijing, China.
  • Wandang Wang
    Department of Clinical Medicine Laboratory, Xiaolan People's Hospital of Zhongshan, Zhongshan, Guangdong, China.

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