Neural Network‐Enabled Multiparametric Impedance Signal Templating for High throughput Single‐Cell Deformability Cytometry Under Viscoelastic Extensional Flows (Small 5/2025)
Source abstract
Abstract
Neural Networks Neural networks that couple the accuracy of cell morphology imaging to the speed of impedance signal templating are presented for extraction of cellular biophysical metrics during flow cytometry to distinguish cellular subpopulations on deformability, viability and electrical physiology properties More in article number 2407212, Federica Caselli, Nathan S. Swami, and co-workers.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Cell Image Analysis Techniques · Microfluidic and Bio-sensing Technologies
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Affiliations
Electrical & Computer Engineering University of Virginia Charlottesville VA 22904 USA
Chemistry, University of Virginia University of Virginia Charlottesville VA 22904 USA
Surgery, School of Medicine University of Virginia Charlottesville VA 22903 USA
Civil Engineering and Computer Science University of Rome Tor Vergata Rome 00133 Italy
References
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