High-Dimensional Analysis of Single-Cell Flow Cytometry Data Predicts Relapse in Childhood Acute Lymphoblastic Leukaemia

High-Dimensional Analysis of Single-Cell Flow Cytometry Data Predicts Relapse in Childhood Acute Lymphoblastic Leukaemia

Artificial intelligence methods may help in unveiling information that is hidden in high-dimensional oncological data. Flow cytometry studies of haematological malignancies provide quantitative data with the potential to be used for the construction of response biomarkers. Many computational methods...

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Bibliographic Details
Main Authors: Salvador Chulián, Álvaro Martínez-Rubio, Víctor M. Pérez-García, María Rosa, Cristina Blázquez Goñi, Juan Francisco Rodríguez Gutiérrez, Lourdes Hermosín-Ramos, Águeda Molinos Quintana, Teresa Caballero-Velázquez, Manuel Ramírez-Orellana, Ana Castillo Robleda, Juan Luis Fernández-Martínez
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Cancers
Subjects:
Acute Lymphoblastic Leukaemia
flow cytometry data
Fisher’s Ratio
CD38
mathematical oncology
response biomarkers
Online Access:https://www.mdpi.com/2072-6694/13/1/17

Internet

https://www.mdpi.com/2072-6694/13/1/17

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