2023
DOI: 10.1016/j.trac.2023.117172
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High-throughput single-cell analysis of nanoparticle-cell interactions

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Cited by 7 publications
(2 citation statements)
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“…Machine learning offers the potential for optimizing parameters and models, significantly reducing processing time [ 154 ]. Moreover, contemporary research in the realm of flow cytometry encompasses cell classification, cell isolation, and their synergistic integration, benefiting from the integration of artificial intelligence techniques and microfluidic methodologies [ 155 ].…”
Section: Future Directions and Challengesmentioning
confidence: 99%
“…Machine learning offers the potential for optimizing parameters and models, significantly reducing processing time [ 154 ]. Moreover, contemporary research in the realm of flow cytometry encompasses cell classification, cell isolation, and their synergistic integration, benefiting from the integration of artificial intelligence techniques and microfluidic methodologies [ 155 ].…”
Section: Future Directions and Challengesmentioning
confidence: 99%
“…Targeted drug delivery, mostly promising in cancer treatment, by magnetic nanoplatforms is related to their interactions at the cellular level, i.e., attachment to the cell, the process of entering it, and its further behavior in the cell [12]. The methods currently used for analyzing interactions at the cell level include flow cytometry, different types of microscopy, and mass spectrometry [13][14][15]. However, these methods have significant limitations, and their applicability is related to specific particles and sensitivity, resolution, and availability, related to technical requirements.…”
Section: Introductionmentioning
confidence: 99%