Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia

Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia

BackgroundNeutrophil extracellular traps (NETs) play pivotal roles in various pathological processes. The formation of NETs is impaired in acute myeloid leukemia (AML), which can result in immunodeficiency and increased susceptibility to infection.MethodsThe gene set variation analysis (GSVA) algori...

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Bibliographic Details
Main Authors: Fangmin Zhong, Fangyi Yao, Zihao Wang, Jing Liu, Bo Huang, Xiaozhong Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Immunology
Subjects:
acute myeloid leukemia
neutrophil extracellular traps
molecular subtypes
machine learning
prognosis
personalized medicine
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2025.1558496/full
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