Abstract
Imaging flow cytometry (IFC) captures multichannel images of hundreds of thousands of single cells within minutes. IFC is seeing a paradigm shift from low- to high-information-content analysis, driven partly by deep learning algorithms. We predict a wealth of applications with potential translation into clinical practice.
Original language | English |
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Pages (from-to) | 649-652 |
Number of pages | 4 |
Journal | Trends in Biotechnology |
Volume | 36 |
Issue number | 7 |
DOIs | |
Publication status | Published - Jul 2018 |
Funding
This work was supported in part by the US National Science Foundation/UK Biotechnology and Biological Sciences Research Council under a joint grant NSF DBI 1458626 and BB/N005163 (A.E.C. and P.R.).
Keywords
- deep learning
- disease diagnostics
- high-content analysis
- imaging flow cytometry
- translational medicine
ASJC Scopus subject areas
- Biotechnology
- Bioengineering