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Updated: Jan 11, 2026
Author Spotlight: Exploring the Mechanisms of MicroRNA Loading into Extracellular Vesicles in Cancer Progression
Published on: October 6, 2023
AI and flow cytometry
Dawei Lin1, Anupama Gururaj1, Sheng Lin-Gibson2
1Division of Allergy, Immunology, and Transplantation, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD 20892, United States.
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.
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