Deciphering impedance cytometry signals with neural networks

  • Federica Caselli
    Department of Civil Engineering and Computer Science, University of Rome Tor Vergata, Rome, Italy
  • Riccardo Reale
    Center for Life Nano Science@Sapienza, Italian Institute of Technology (IIT), Rome, Italy
  • Adele De Ninno
    Italian National Research Council - Institute for Photonics and Nanotechnologies (CNR - IFN), Rome, Italy
  • Daniel Spencer
    School of Electronics and Computing Science, and, Institute for Life Sciences, University of Southampton, Highfield, Southampton, UK
  • Hywel Morgan
    School of Electronics and Computing Science, and, Institute for Life Sciences, University of Southampton, Highfield, Southampton, UK
  • Paolo Bisegna
    Department of Civil Engineering and Computer Science, University of Rome Tor Vergata, Rome, Italy

抄録

<jats:p>A successful outcome of the coupling between microfluidics and AI: neural networks tackle the signal processing challenges of single-cell microfluidic impedance cytometry.</jats:p>

収録刊行物

  • Lab on a Chip

    Lab on a Chip 22 (9), 1714-1722, 2022

    Royal Society of Chemistry (RSC)

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