Feature genes predicting the FLT3/ITD mutation in acute myeloid leukemia
In the present study, gene expression profiles of acute myeloid leukemia (AML) samples were analyzed to identify feature genes with the capacity to predict the mutation status of FLT3/ITD. Two machine learning models, namely the support vector machine (SVM) and random forest (RF) methods, were used...
| Main Authors: | , , , |
|---|---|
| Format: | Online |
| Language: | English |
| Published: |
D.A. Spandidos
2016
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4918602/ |