Using machine learning tools to detect gene mutations from leukemia cell images
Gene mutations in acute myeloid leukemia (AML) cells can guide treatment options, and machine learning can rapidly guess the ...
Nature5y
Mutations in patients with cytogenetically normal AML predict treatment outcome
The authors recommend that newly diagnosed patients with AML should be screened for NPM1, FLT3, and CEBPA mutations, as the data from such analyses provide important prognostic information and may ...
Medscape18d
Genetic Biomarkers in Acute Myeloid Leukemia
The routine incorporation of NPM1, FLT3 and perhaps CEBPA-DM mutational testing can now be strongly recommended in addition to a standard karyotype evaluation. Patients with normal cytogenetics ...
Nature2mon
Impact of pre-transplant MRD on AML prognosis
to predict post-transplant relapse and survival compared to flow cytometry in patients with FLT3-ITD or NPM1 mutated AML. The current collection of manuscripts presents additional original data ...
Medscape15d
Genetic Biomarkers in Acute Myeloid Leukemia
Risk categorization of AML based on karyotyping of leukemic blasts has become routine. Mutations in NPM1, CCAAT enhancer-binding protein-α (with double-mutations) and FCT3-internal tandem ...