|
Research
Agentic AI in Flow Cytometry: Why the Next Revolution Isn't Another Algorithm — It's an Agent
Flow cytometry analysis is evolving from manual gating to ML-automated classification. But the real paradigm shift is agentic AI — autonomous systems that reason, search literature, and generate publication-ready reports. This report maps the competitive landscape and identifies the gap no one has filled: PubMed-integrated agentic flow cytometry analysis.
References
- [1] Applications of machine learning for immunophenotypic MRD assessment in AML PMID: 40400510
- [2] AI in flow cytometry: Current applications and future directions PMID: 40985220
- [3] Clinical validation of a real-time ML system for AML detection by flow cytometry PMID: 40016870
- [4] Validation of AI-Assisted Flow Cytometry Analysis for Immunological Disorders https://pmc.ncbi.nlm.nih.gov/articles/PMC10888253/
- [5] AHEAD Medicine Cyto-copilot Platform https://aheadmedicine.com/
- [6] OMIQ Flow Cytometry Software Platform https://www.omiq.ai/features/flow-cytometry-software
- [7] diagnFlow: ML for any hematologic flow cytometry dataset PMID: 41160786
- [8] AutoFlow: Interactive Shiny app for flow cytometry analysis PMID: 41692956
- [9] Multi-instance learning framework in flow cytometry PMID: 41526550
- [10] Automated Gating of CD34 Cells: ML-Based ISHAGE Protocol PMID: 41720619
- [11] Streamline automated biomedical discoveries with agentic bioinformatics https://pmc.ncbi.nlm.nih.gov/articles/PMC12476841/
- [12] CellAtria: Agentic AI framework for single-cell RNA-seq analysis https://www.nature.com/articles/s44387-025-00064-0
- [13] Clinical-grade autonomous cytopathology through whole-slide edge tomography PMID: 41708854