Processing code-multiplexed Coulter signals via deep convolutional neural networks

Abstract

Deep learning-enhanced Coulter counter networks for electronic tracking of particles in microfluidic devices.

A neural network approach for real-time particle/cell characterization in microfluidic impedance cytometry

“…Their accuracy has been assessed in our previous works [7,37,44]. Alternatively, features computed by means of image processing could be used [33]. However, the latter approach requires high-speed image acquisition systems and the estimation of cell properties is not always straightforward, due to possible motion blurring, low contrast, and limited spatial resolution.…”

“…Applications to real-time analysis of unidimensional signals (as opposite to bidimensional images) have also been widely reported in biomedical signal analysis, such as human activity recognition from accelerometer data [29], sleep stage classification from EEG signals [30], patient-specific ECG classification [31], and diabetes detection from breath signals obtained from gas sensors [32]. Recently, Wang et al [33] used a deep convolutional neural network to analyze codemultiplexed signals from a Coulter sensor network.…”

Combinatorial Immunophenotyping of Cell Populations with an Electronic Antibody Microarray

“…In fact, computational analysis of the assay results could be performed in real-time (~1000 cells s -1 ) using deep learning algorithms. [48] Overall, our platform operates as simple as a Coulter counter supported with more advanced software to interpret its results. Third, our assay is both flexible and scalable to screen for a specific and larger number of antigen combinations, respectively.…”

Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks

“…Firstly, there is rather fragmentarily available literature involving DL algorithms for TSP prediction, and Secondly, there appear to be gaps in TSP prediction application in Australia despite a handful of studies performed elsewhere, e.g. TSP concentration models in China sea with back-propagation neural network (BPNN) [20], multi-layer filtration system [21], modelling TSP with light scattering [22], and with coulter sensors [23]. However, none of these studies have forecasted TSP w.r.t air quality.…”