期刊
BRITISH JOURNAL OF HAEMATOLOGY
卷 -, 期 -, 页码 -出版社
WILEY
DOI: 10.1111/bjh.18833
关键词
AI; CLL; flow cytometry; machine learning; MRD
类别
The study shows that AI-based methods can improve flow cytometry diagnostics in haematology. By exploring an emerging machine learning approach, the research demonstrates that AI-driven computational analysis may be a robust and feasible tool for advanced diagnostics of haematological malignancies.
The era of AI-based methods to improve flow cytometry diagnostics in haematology is now at the beginning. The study by Nguyen and colleagues explored an emerging machine learning approach to assess phenotypic MRD in chronic lymphocytic leukaemia patients, showing that such AI-driven computational analysis may represent a robust and feasible tool for advanced diagnostics of haematological malignancies. Commentary on: Nguyen et al. Computational flow cytometry provides accurate assessment of measurable residual disease in chronic lymphocytic leukaemia. Br J Haematol 2023 (Online ahead of print). doi:
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