Space-time-regulated imaging analyzer for smart coagulation diagnosis.

Journal: Cell reports. Medicine
PMID: 36206751

Abstract

The development of intelligent blood coagulation diagnoses is awaited to meet the current need for large clinical time-sensitive caseloads due to its efficient and automated diagnoses. Herein, a method is reported and validated to realize it through artificial intelligence (AI)-assisted optical clotting biophysics (OCB) properties identification. The image differential calculation is used for precise acquisition of OCB properties with elimination of initial differences, and the strategy of space-time regulation allows on-demand space time OCB properties identification and enables diverse blood function diagnoses. The integrated applications of smartphones and cloud computing offer a user-friendly automated analysis for accurate and convenient diagnoses. The prospective assays of clinical cases (n = 41) show that the system realizes 97.6%, 95.1%, and 100% accuracy for coagulation factors, fibrinogen function, and comprehensive blood coagulation diagnoses, respectively. This method should enable more low-cost and convenient diagnoses and provide a path for potential diagnostic-markers finding.

Authors

  • Longfei Chen
    College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao, China.
  • Le Yu
    Tobacco Research Institute, Chinese Academy of Agricultural Sciences, Qingdao, China.
  • Yantong Liu
    Key Laboratory of Artificial Micro- and Nano- Structures of Ministry of Education, School of Physics & Technology, Wuhan University, Wuhan 430072, China; Renmin Hospital, Wuhan University, Wuhan 430060, China; Shenzhen Research Institute, Wuhan University, Shenzhen 518000, China.
  • Hongshan Xu
    Key Laboratory of Artificial Micro- and Nano- Structures of Ministry of Education, School of Physics & Technology, Wuhan University, Wuhan 430072, China.
  • Linlu Ma
    Department of Hematology, Zhongnan Hospital, Wuhan University, Wuhan 430071, China.
  • Pengfu Tian
    Key Laboratory of Artificial Micro- and Nano- Structures of Ministry of Education, School of Physics & Technology, Wuhan University, Wuhan 430072, China.
  • Jiaomeng Zhu
    Key Laboratory of Artificial Micro- and Nano- Structures of Ministry of Education, School of Physics & Technology, Wuhan University, Wuhan 430072, China.
  • Fang Wang
    Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education and Hunan Key Laboratory for Computation and Simulation in Science and Engineering, Xiangtan University, Xiangtan, China.
  • Kezhen Yi
    Department of Laboratory Medicine, Zhongnan Hospital, Wuhan University, Wuhan 430071, China.
  • Hui Xiao
    Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, People's Republic of China.
  • Fuling Zhou
    Department of Hematology, Zhongnan Hospital, Wuhan University, Wuhan 430071, China.
  • Yi Yang
    Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
  • Yanxiang Cheng
    Renmin Hospital, Wuhan University, Wuhan 430060, China.
  • Long Bai
    State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China. bailong@cqu.edu.cn.
  • Fubing Wang
    Department of Laboratory Medicine, Zhongnan Hospital, Wuhan University, Wuhan 430071, China.
  • Yimin Zhu
    Dalian Maritime University China yyang@dlmu.edu.cn zhaojiao@dlmu.edu.cn ntp@dlmu.edu.cn.

Keywords

External Resources

Popular Topics
Recent Journals