Clinically validated machine learning algorithm for detecting residual diseases with multicolor flow cytometry analysis in acute myeloid leukemia and myelodysplastic syndrome

BACKGROUND: Multicolor flow cytometry (MFC) analysis is widely used to identify minimal residual disease (MRD) after treatment for acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). However, current manual interpretation suffers from drawbacks of time consuming and interpreter idiosync...

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Detalles Bibliográficos
Autores principales: Ko, Bor-Sheng, Wang, Yu-Fen, Li, Jeng-Lin, Li, Chi-Cheng, Weng, Pei-Fang, Hsu, Szu-Chun, Hou, Hsin-An, Huang, Huai-Hsuan, Yao, Ming, Lin, Chien-Ting, Liu, Jia-Hau, Tsai, Cheng-Hong, Huang, Tai-Chung, Wu, Shang-Ju, Huang, Shang-Yi, Chou, Wen-Chien, Tien, Hwei-Fang, Lee, Chi-Chun, Tang, Jih-Luh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Research paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6284584/
https://www.ncbi.nlm.nih.gov/pubmed/30361063
http://dx.doi.org/10.1016/j.ebiom.2018.10.042

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6284584/
https://www.ncbi.nlm.nih.gov/pubmed/30361063
http://dx.doi.org/10.1016/j.ebiom.2018.10.042

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