TY  - JOUR 
AU  - Mosquera Orgueira, Adrián
AU  - Pérez Encinas, Manuel Mateo
AU  - Diaz Varela, N.A.
AU  - Mora, E.
AU  - Díaz-Beyá, M.
AU  - Montoro, M.J.
AU  - Pomares, H.
AU  - Ramos, F.
AU  - Tormo, M.
AU  - Jerez, A.
AU  - Nomdedeu, J.F.
AU  - De Miguel Sanchez, C.
AU  - Leonor, A.
AU  - Cárcel, P.
AU  - Cedena Romero, M.T.
AU  - Xicoy, B.
AU  - Rivero, E.
AU  - Del Orbe Barreto, R.A.
AU  - Diez-Campelo, M.
AU  - Benlloch, L.E.
AU  - Crucitti, D.
AU  - Valcárcel, D.
PY  - 2023
SN  - 2572-9241
UR  - http://hdl.handle.net/20.500.11940/21699
AB  - Myelodysplastic neoplasms (MDS) are a heterogeneous group of hematological stem cell disorders characterized by dysplasia, cytopenias, and increased risk of acute leukemia. As prognosis differs widely between patients, and treatment options vary from...
LA  - eng
TI  - Machine Learning Improves Risk Stratification in Myelodysplastic Neoplasms: An Analysis of the Spanish Group of Myelodysplastic Syndromes
DO  - 10.1097/hs9.0000000000000961
T2  - HemaSphere
M2  - E961
KW  - AS Santiago
KW  - CHUS
KW  - AS Santiago
KW  - CHUS
VL  - 7
ER  -