The Role of AI in Image Analysis for Flow Cytometry. Artificial intelligence (AI) and machine learning (ML) are transforming flow cytometry, specifically IFC, by significantly improving data analysis.

Automated analysis of cytometry data has been advanced significantly by a variety of flow cytometry-specific clustering algorithms, which can be integrated as part of a workflow leveraging FlowJo ...

The company’s new CytoML Experiment Suite fully automates each stage of the flow cytometry data lifecycle, allowing for clearer data visualization and analysis. A new data analysis suite by Aigenpulse ...

LEGENDplex™ software is a robust data analysis package that automates flow cytometry data analysis and performs clustering analysis with the highest level of speed, accuracy, and reliability. Analysis ...

In this analysis, the authors directly compared the performance of flow cytometry data processing algorithms to manual gating approaches. The results offer information of practical utility about ...

With terraFlow, upload cytometry data, label patient groups, and hit submit. In 24 hours you get back a complete, presentation-ready preprint of your data. Our exhaustive approach evaluates every ...

Classifying flow cytometry data using Bayesian analysis helps to distinguish ALS patients from healthy controls Saskia Räuber 1*† Christopher Nelke 1† Christina B. Schroeter 1 Sumanta Barman 1 Marc ...

Global flow cytometry market was valued at $7.05 billion in 2021, and it is expected to reach a value of $12.98 billion by 2028, at a CAGR of 9.10% over the forecast period (2022 - 2028).Westford ...

The time-of-flight of the ions from the sample to the detector is used for the analysis. Spectral flow cytometry 3: ... (SPADE), 7 and t-stochastic neighbor embedding (tSNE) algorithms. 8 These ...

Flow cytometry analysis expanded into the clinical setting by helping streamline the quantification of CD4 + T cells during the human immunodeficiency virus (HIV) epidemic. Compared to microscopy, ...