From gating to computational flow cytometry: Exploiting artificial intelligence for MRD diagnostics.
Br J Haematol
; 202(4): 715-717, 2023 08.
Article
en En
| MEDLINE
| ID: mdl-37092558
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;202760-770.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Leucemia Linfocítica Crónica de Células B
/
Neoplasias Hematológicas
Tipo de estudio:
Diagnostic_studies
Límite:
Humans
Idioma:
En
Revista:
Br J Haematol
Año:
2023
Tipo del documento:
Article
País de afiliación:
Italia