Alice Yue, Ryan R. Brinkman, Veronica Nash, Fabian Junker, Goce Bogdanoski, Anagha Divekar, Aaron Tyznik, Josef Spidlen, Wolfgang Kern, Jordi Petriz, Kaska Wloka, Kamila Czechowska
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AI in flow cytometry: Current applications and future directions
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.
期刊介绍:
Cytometry Part B: Clinical Cytometry features original research reports, in-depth reviews and special issues that directly relate to and palpably impact clinical flow, mass and image-based cytometry. These may include clinical and translational investigations important in the diagnostic, prognostic and therapeutic management of patients. Thus, we welcome research papers from various disciplines related [but not limited to] hematopathologists, hematologists, immunologists and cell biologists with clinically relevant and innovative studies investigating individual-cell analytics and/or separations. In addition to the types of papers indicated above, we also welcome Letters to the Editor, describing case reports or important medical or technical topics relevant to our readership without the length and depth of a full original report.