Review analyzes AI's role in improving flow cytometry applications in diagnostics and research, suggesting new integrations.
Flow cytometry is a powerful tool for analyzing diverse cellular properties, making it essential in immunology research, clinical trials, and diagnostics. Integrating artificial intelligence (AI) into flow cytometry has the potential to enhance various aspects of assay development and application, including reagent selection, instrument standardization, panel and assay design, data analysis, quality controls, and knowledge dissemination. This paper provides a review of current AI applications in flow cytometry and explores the potential future directions for AI integration in the field.
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Yue et al. (2025) studied this question.
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