Use of a hybrid intelligence decision tree to identify mature B-cell neoplasms.

Autor: Vergnolle I; Laboratoire d'Hématologie, Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopole, Toulouse, France., Ceccomarini T; Laboratoire d'Hématologie, Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopole, Toulouse, France., Canali A; Laboratoire d'Hématologie, Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopole, Toulouse, France., Rieu JB; Laboratoire d'Hématologie, Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopole, Toulouse, France., Vergez F; Laboratoire d'Hématologie, Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopole, Toulouse, France.; Université Toulouse III Paul Sabatier, Toulouse, France.; Cancer Research Center of Toulouse, UMR1037 INSERM, ERL5294 CNRS, Toulouse, France.
Jazyk: angličtina
Zdroj: Cytometry. Part B, Clinical cytometry [Cytometry B Clin Cytom] 2023 Aug 04. Date of Electronic Publication: 2023 Aug 04.
DOI: 10.1002/cyto.b.22136
Abstrakt: Background: Mature B-cell neoplasms are challenging to diagnose due to their heterogeneity and overlapping clinical and biological features. In this study, we present a new workflow strategy that leverages a large amount of flow cytometry data and an artificial intelligence approach to classify these neoplasms.
Methods: By combining mathematical tools, such as classification algorithms and regression tree (CART) models, with biological expertise, we have developed a decision tree that accurately identifies mature B-cell neoplasms. This includes chronic lymphocytic leukemia (CLL), for which cytometry has been extensively used, as well as other non-CLL subtypes.
Results: The decision tree is easy to use and proposes a diagnosis and classification of mature B-cell neoplasms to the users. It can identify the majority of CLL cases using just three markers: CD5, CD43, and CD200.
Conclusion: This approach has the potential to improve the accuracy and efficiency of mature B-cell neoplasm diagnosis.
(© 2023 The Authors. Cytometry Part B: Clinical Cytometry published by Wiley Periodicals LLC on behalf of International Clinical Cytometry Society.)
Databáze: MEDLINE
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