AIMC Topic: Flow Cytometry

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flowSim: Near duplicate detection for flow cytometry data.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Aug 29, 2023
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...
Algorithms Flow Cytometry Cluster Analysis Machine Learning
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Real-time fluorescence imaging flow cytometry enabled by motion deblurring and deep learning algorithms.

Lab on a chip Aug 8, 2023
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...
Algorithms Deep Learning Humans HeLa Cells Image Processing, Computer-Assisted Optical Imaging Flow Cytometry
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Acute psychological stress-induced progenitor cell mobilization and cardiovascular events.

Journal of psychosomatic research Jun 14, 2023
OBJECTIVE: Certain brain activation responses to psychological stress are associated with worse outcomes in CVD patients. We hypothesized that elevated acute psychological stress, manifesting as greater activity within neural centers for emotional re...
Flow Cytometry Myocardial Infarction Coronary Artery Disease Stress, Psychological Humans Antigens, CD34 Stem Cells
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Artificial Intelligence for Clinical Flow Cytometry.

Clinics in laboratory medicine May 29, 2023
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...
Flow Cytometry Machine Learning Artificial Intelligence
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A review on intelligent impedance cytometry systems: Development, applications and advances.

Analytica chimica acta May 29, 2023
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...
Machine Learning Flow Cytometry Electric Impedance
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Optical time-stretch imaging flow cytometry in the compressed domain.

Journal of biophotonics May 18, 2023
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...
Single-Cell Analysis Flow Cytometry Machine Learning Optical Imaging Microfluidics
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Label-free liquid biopsy through the identification of tumor cells by machine learning-powered tomographic phase imaging flow cytometry.

Scientific reports Apr 13, 2023
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...
Tomography Flow Cytometry Humans Liquid Biopsy Neoplastic Cells, Circulating Machine Learning Artificial Intelligence
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Cell damage evaluation by intelligent imaging flow cytometry.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Mar 31, 2023
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...
Leukocytes Optical Imaging Algorithms Flow Cytometry Machine Learning
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Artificial intelligence in clinical multiparameter flow cytometry and mass cytometry-key tools and progress.

Seminars in diagnostic pathology Mar 5, 2023
There are many research studies and emerging tools using artificial intelligence (AI) and machine learning to augment flow and mass cytometry workflows. Emerging AI tools can quickly identify common cell populations with continuous improvement of acc...
Humans Flow Cytometry Machine Learning Artificial Intelligence Algorithms
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Automated quantification of measurable residual disease in chronic lymphocytic leukemia using an artificial intelligence-assisted workflow.

Cytometry. Part B, Clinical cytometry Feb 23, 2023
Detection of measurable residual disease (MRD) in chronic lymphocytic leukemia (CLL) is an important prognostic marker. The most common CLL MRD method in current use is multiparameter flow cytometry, but availability is limited by the need for expert...
Humans Artificial Intelligence Workflow Leukemia, Lymphocytic, Chronic, B-Cell Flow Cytometry Neoplasm, Residual
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