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Flow Cytometry

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[Artificial intelligence-based fluorescence method versus traditional flow cytometry in detection of sperm DNA fragmentation index].

Zhonghua nan ke xue = National journal of andrology
OBJECTIVE: To compare the result of the artificial intelligence (AI) recognition-based fluorescence method and that of traditional flow cytometry in the examination of the sperm DNA fragmentation index (DFI) and assess the reliability of the AI-based...

Cell damage evaluation by intelligent imaging flow cytometry.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Essential thrombocythemia (ET) is an uncommon situation in which the body produces too many platelets. This can cause blood clots anywhere in the body and results in various symptoms and even strokes or heart attacks. Removing excessive platelets usi...

Label-free liquid biopsy through the identification of tumor cells by machine learning-powered tomographic phase imaging flow cytometry.

Scientific reports
Image-based identification of circulating tumor cells in microfluidic cytometry condition is one of the most challenging perspectives in the Liquid Biopsy scenario. Here we show a machine learning-powered tomographic phase imaging flow cytometry syst...

Artificial Intelligence for Clinical Flow Cytometry.

Clinics in laboratory medicine
In this review, the authors discuss the fundamental principles of machine learning. They explore recent studies and approaches in implementing machine learning into flow cytometry workflows. These applications are promising but not without their shor...

A review on intelligent impedance cytometry systems: Development, applications and advances.

Analytica chimica acta
Impedance cytometry is a well-established technique for counting and analyzing single cells, with several advantages, such as convenience, high throughput, and no labeling required. A typical experiment consists of the following steps: single-cell me...

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...

flowSim: Near duplicate detection for flow cytometry data.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
The analysis of large amounts of data is important for the development of machine learning (ML) models. flowSim is the first algorithm designed to visualize, detect and remove highly redundant information in flow cytometry (FCM) training sets to decr...

Real-time fluorescence imaging flow cytometry enabled by motion deblurring and deep learning algorithms.

Lab on a chip
Fluorescence imaging flow cytometry (IFC) has been demonstrated as a crucial biomedical technique for analyzing specific cell subpopulations from heterogeneous cellular populations. However, the high-speed flow of fluorescent cells leads to motion bl...

Label-Free Intracellular Multi-Specificity in Yeast Cells by Phase-Contrast Tomographic Flow Cytometry.

Small methods
In-flow phase-contrast tomography provides a 3D refractive index of label-free cells in cytometry systems. Its major limitation, as with any quantitative phase imaging approach, is the lack of specificity compared to fluorescence microscopy, thus res...

Deductive automated pollen classification in environmental samples via exploratory deep learning and imaging flow cytometry.

The New phytologist
Pollen and tracheophyte spores are ubiquitous environmental indicators at local and global scales. Palynology is typically performed manually by microscopic analysis; a specialised and time-consuming task limited in taxonomical precision and sampling...