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:
From gating to computational flow cytometry: Exploiting artificial intelligence for MRD diagnostics / Riva, Giovanni; Luppi, Mario; Tagliafico, Enrico. - In: BRITISH JOURNAL OF HAEMATOLOGY. - ISSN 0007-1048. - 202:4(2023), pp. 715-717. [10.1111/bjh.18833]
From gating to computational flow cytometry: Exploiting artificial intelligence for MRD diagnostics
Riva, Giovanni
;Luppi, Mario;Tagliafico, Enrico
2023
Abstract
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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