AIMC Topic: Microfluidics

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Advance of microfluidic flow cytometry enabling high-throughput characterization of single-cell electrical and structural properties.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
This paper reported a micro flow cytometer capable of high-throughput characterization of single-cell electrical and structural features based on constrictional microchannels and deep neural networks. When single cells traveled through microchannels ...

Artificial intelligence-accelerated high-throughput screening of antibiotic combinations on a microfluidic combinatorial droplet system.

Lab on a chip
Microfluidic platforms have been employed as an effective tool for drug screening and exhibit the advantages of lower reagent consumption, higher throughput and a higher degree of automation. Despite the great advancement, it remains challenging to s...

iCLOTS: open-source, artificial intelligence-enabled software for analyses of blood cells in microfluidic and microscopy-based assays.

Nature communications
While microscopy-based cellular assays, including microfluidics, have significantly advanced over the last several decades, there has not been concurrent development of widely-accessible techniques to analyze time-dependent microscopy data incorporat...

Computer Vision-Based Artificial Intelligence-Mediated Encoding-Decoding for Multiplexed Microfluidic Digital Immunoassay.

ACS nano
Digital immunoassays with multiplexed capacity, ultrahigh sensitivity, and broad affordability are urgently required in clinical diagnosis, food safety, and environmental monitoring. In this work, a multidimensional digital immunoassay has been devel...

Optical time-stretch imaging flow cytometry in the compressed domain.

Journal of biophotonics
Imaging flow cytometry based on optical time-stretch (OTS) imaging combined with a microfluidic chip attracts much attention in the large-scale single-cell analysis due to its high throughput, high precision, and label-free operation. Compressive sen...

High-throughput cell spheroid production and assembly analysis by microfluidics and deep learning.

SLAS technology
3D cell culture models are important tools in translational research but have been out of reach for high-throughput screening due to complexity, requirement of large cell numbers and inadequate standardization. Microfluidics and culture model miniatu...

Paper microfluidics with deep learning for portable intelligent nucleic acid amplification tests.

Talanta
During global outbreaks such as COVID-19, regular nucleic acid amplification tests (NAATs) have posed unprecedented burden on hospital resources. Data of traditional NAATs are manually analyzed post assay. Integration of artificial intelligence (AI) ...

The Synergy between Deep Learning and Organs-on-Chips for High-Throughput Drug Screening: A Review.

Biosensors
Organs-on-chips (OoCs) are miniature microfluidic systems that have arguably become a class of advanced in vitro models. Deep learning, as an emerging topic in machine learning, has the ability to extract a hidden statistical relationship from the in...

Nucleic Acid Quantification by Multi-Frequency Impedance Cytometry and Machine Learning.

Biosensors
Determining nucleic acid concentrations in a sample is an important step prior to proceeding with downstream analysis in molecular diagnostics. Given the need for testing DNA amounts and its purity in many samples, including in samples with very smal...

Research on cell detection method for microfluidic single cell dispensing.

Mathematical biosciences and engineering : MBE
Single cell dispensing techniques mainly include limiting dilution, fluorescent-activated cell sorting (FACS) and microfluidic approaches. Limiting dilution process is complicated by statistical analysis of clonally derived cell lines. Flow cytometry...