Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia
The NET-related signature, derived from a combination of diverse machine learning algorithms, has promising potential as a valuable tool for prognostic prediction, preventive measures, and personalized medicine in patients with AML.
Authors
- Xiaozhong Wang (ORCID: https://orcid.org/0000-0001-8152-8971)
- Bo Huang (ORCID: https://orcid.org/0000-0002-3228-7662)
- Fangyi Yao
- Jing Liu (ORCID: https://orcid.org/0000-0001-9513-3591)
- Fangmin Zhong
- Zi-Hao Wang (ORCID: https://orcid.org/0000-0001-6368-2158)
Institutions
- Nanchang University (CN)
- First Affiliated Hospital of Jiangxi Medical College (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2025-02-24
- DOI
- https://doi.org/10.3389/fimmu.2025.1558496
- Citations
- 6
- Primary Topic
- Neutrophil, Myeloperoxidase and Oxidative Mechanisms
- Type
- article
- Field-Weighted Citation Impact
- 4.78