Development and validation of a cuproptosis-related prognostic model for acute myeloid leukemia patients using machine learning with stacking

Development and validation of a cuproptosis-related prognostic model for acute myeloid leukemia patients using machine learning with stacking

Abstract Our objective is to develop a prognostic model focused on cuproptosis, aimed at predicting overall survival (OS) outcomes among Acute myeloid leukemia (AML) patients. The model utilized machine learning algorithms incorporating stacking. The GSE37642 dataset was used as the training data, a...

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Bibliographic Details
Main Authors: Xichao Wang, Hao Sun, Yongfei Dong, Jie Huang, Lu Bai, Zaixiang Tang, Songbai Liu, Suning Chen
Format: Article
Language:English
Published: Nature Portfolio 2024-02-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-024-53306-7

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https://doi.org/10.1038/s41598-024-53306-7

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