TY  - JOUR
AU  - Chulián, Salvador
AU  - Martínez-Rubio, Álvaro
AU  - Pérez-García, Víctor M
AU  - Rosa, María
AU  - Blázquez Goñi, Cristina
AU  - Rodríguez Gutiérrez, Juan Francisco
AU  - Hermosín-Ramos, Lourdes
AU  - Molinos Quintana, Águeda
AU  - Caballero-Velázquez, Teresa
AU  - Ramírez-Orellana, Manuel
AU  - Castillo Robleda, Ana
AU  - Fernández-Martínez, Juan Luis
PY  - 2020
DO  - 10.3390/cancers13010017
SN  - 2072-6694
UR  - https://hdl.handle.net/10668/25117
T2  - Cancers
AB  - 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...
LA  - en
KW  - Acute Lymphoblastic Leukaemia
KW  - CD38
KW  - Fisher’s Ratio
KW  - flow cytometry data
KW  - mathematical oncology
KW  - personalised medicine
KW  - response biomarkers
TI  - High-Dimensional Analysis of Single-Cell Flow Cytometry Data Predicts Relapse in Childhood Acute Lymphoblastic Leukaemia.
TY  - research article
VL  - 13
ER  -