Open AccessPrediction of complete remission and survival in acute myeloid leukemia using supervised machine learning
Author(s) -
Jan-Niklas Eckardt,
Christoph Röllig,
Klaus H. Metzeler,
Michael Kramer,
Sebastian Stasik,
Julia-Annabell Georgi,
Peter Heisig,
Karsten Spiekermann,
Utz Krug,
Jan Braess,
Dennis Görlich,
Cristina Sauerland,
Bernhard J. Woermann,
Tobias Herold,
Wolfgang E. Berdel,
Wolfgang Hiddemann,
Frank Kroschinsky,
Johannes Schetelig,
Uwe Platzbecker,
Carsten MüllerTidow,
Tim Sauer,
Hubert Serve,
Claudia D. Baldus,
Kerstin SchäferEckart,
Martin Kaufmann,
Stefan W. Krause,
Mathias Hänel,
Christoph Schliemann,
Maher Hanoun,
Christian Thiede,
Martin Bornhäuser,
Karsten Wendt,
Jan Moritz Middeke
Publication year - 2022
Publication title -
haematologica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.782
H-Index - 142
eISSN - 1592-8721
pISSN - 0390-6078
DOI - 10.3324/haematol.2021.280027
Subject(s) - cebpa , npm1 , medicine , oncology , myeloid leukemia , cohort , biology , karyotype , mutation , genetics , chromosome , gene