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Space-time-regulated imaging analyzer for smart coagulation diagnosis

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 clot...

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Detalles Bibliográficos
Autores principales: Chen, Longfei, Yu, Le, Liu, Yantong, Xu, Hongshan, Ma, Linlu, Tian, Pengfu, Zhu, Jiaomeng, Wang, Fang, Yi, Kezhen, Xiao, Hui, Zhou, Fuling, Yang, Yi, Cheng, Yanxiang, Bai, Long, Wang, Fubing, Zhu, Yimin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9589004/
https://www.ncbi.nlm.nih.gov/pubmed/36206751
http://dx.doi.org/10.1016/j.xcrm.2022.100765
Descripción
Sumario: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.