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Review
. 2026 Feb 9;215(2):vkaf292.
doi: 10.1093/jimmun/vkaf292.

AI and flow cytometry

Affiliations
Review

AI and flow cytometry

Dawei Lin et al. J Immunol. .

Abstract

Artificial intelligence (AI) and machine learning (ML) are transforming biotechnology and playing a key role in bioeconomy. One of the most important measurement capabilities at the forefront of biotechnology innovations is flow cytometry (FCM), a high-throughput, single-cell analysis platform technology. However, the quality and consistency of FCM data can vary significantly across laboratories and study datasets, resulting in millions of FCM datasets siloed for their use in AI applications. This workshop focuses on overcoming challenges and identifying solutions that include essential measurements, reference controls, AI-ready reference data, and current AI/ML models. It aims to advance AI/ML applications in FCM and related data.

Keywords: Artificial intelligence (AI) and machine learning (ML) models, Experimental design incorporating reference materials; Data repositories and data standards; Flow cytometry (FCM); translational and clinical applications.

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