AIMC Topic: Flow Cytometry

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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...

High-content video flow cytometry with digital cell filtering for label-free cell classification by machine learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Recent development of imaging flow cytometry (IFC) has enabled the measurements of single cells with high throughput, where fluorescent labels provide specificity for cellular diagnosis. The fluorescent labels may disturb the cell functions, and the ...

Toward five-part differential of leukocytes based on electrical impedances of single cells and neural network.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
The five-part differential of leukocytes plays key roles in the diagnosis of a variety of diseases and is realized by optical examinations of single cells, which is prone to various artifacts due to chemical treatments. The classification of leukocyt...

Artificial intelligence-based classification of peripheral blood nucleated cells using label-free imaging flow cytometry.

Lab on a chip
Label-free image identification of circulating rare cells, such as circulating tumor cells within peripheral blood nucleated cells (PBNCs), the vast majority of which are white blood cells (WBCs), remains challenging. We previously described developi...

Combining imaging flow cytometry and machine learning for high-throughput schistocyte quantification: A SVM classifier development and external validation cohort.

EBioMedicine
BACKGROUND: Schistocyte counts are a cornerstone of the diagnosis of thrombotic microangiopathy syndrome (TMA). Their manual quantification is complex and alternative automated methods suffer from pitfalls that limit their use. We report a method com...

Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry.

Cells
Cellular senescence is a hallmark of aging and a promising target for therapeutic approaches. The identification of senescent cells requires multiple biomarkers and complex experimental procedures, resulting in increased variability and reduced sensi...

Intelligent sort-timing prediction for image-activated cell sorting.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Intelligent image-activated cell sorting (iIACS) has enabled high-throughput image-based sorting of single cells with artificial intelligence (AI) algorithms. This AI-on-a-chip technology combines fluorescence microscopy, AI-based image processing, s...

Diagnostic accuracy of fluorescence flow-cytometry technology using Sysmex XN-31 for imported malaria in a non-endemic setting.

Parasite (Paris, France)
Malaria diagnosis based on microscopy is impaired by the gradual disappearance of experienced microscopists in non-endemic areas. Aside from the conventional diagnostic methods, fluorescence flow cytometry technology using Sysmex XN-31, an automated ...

Deciphering impedance cytometry signals with neural networks.

Lab on a chip
Microfluidic impedance cytometry is a label-free technique for high-throughput single-cell analysis. Multi-frequency impedance measurements provide data that allows full characterisation of cells, linking electrical phenotype to individual biophysica...

Prediction of standard cell types and functional markers from textual descriptions of flow cytometry gating definitions using machine learning.

Cytometry. Part B, Clinical cytometry
BACKGROUND: A key step in clinical flow cytometry data analysis is gating, which involves the identification of cell populations. The process of gating produces a set of reportable results, which are typically described by gating definitions. The non...