Automation in Flow Cytometry.
Artificial intelligence
Automation
Flow cytometry
Sample handling
Throughput
Turnaround time
Journal
Clinics in laboratory medicine
ISSN: 1557-9832
Titre abrégé: Clin Lab Med
Pays: United States
ID NLM: 8100174
Informations de publication
Date de publication:
Sep 2024
Sep 2024
Historique:
medline:
2
8
2024
pubmed:
2
8
2024
entrez:
1
8
2024
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 39089751
pii: S0272-2712(24)00018-0
doi: 10.1016/j.cll.2024.04.007
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
455-463Informations de copyright
Copyright © 2024 Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Disclosure The authors have nothing to disclose.