Artificial Intelligence Enhances Diagnostic Flow Cytometry Workflow in the Detection of Minimal Residual Disease of Chronic Lymphocytic Leukemia

SIMPLE SUMMARY: Flow cytometric immunophenotyping is critical in detecting minimal residual disease (MRD) in patients with chronic lymphocytic leukemia (CLL). However, flow cytometric analysis is complicated and time-consuming. Herein, we evaluated the performance of a deep neural network (DNN) in d...

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Detalles Bibliográficos
Autores principales: Salama, Mohamed E., Otteson, Gregory E., Camp, Jon J., Seheult, Jansen N., Jevremovic, Dragan, Holmes, David R., Olteanu, Horatiu, Shi, Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139233/
https://www.ncbi.nlm.nih.gov/pubmed/35626140
http://dx.doi.org/10.3390/cancers14102537

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139233/
https://www.ncbi.nlm.nih.gov/pubmed/35626140
http://dx.doi.org/10.3390/cancers14102537

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