Integrated machine learning survival framework develops a prognostic model based on inter-crosstalk definition of mitochondrial function and cell death patterns in a large multicenter cohort for lower-grade glioma

Integrated machine learning survival framework develops a prognostic model based on inter-crosstalk definition of mitochondrial function and cell death patterns in a large multicenter cohort for lower-grade glioma

Abstract Background Lower-grade glioma (LGG) is a highly heterogeneous disease that presents challenges in accurately predicting patient prognosis. Mitochondria play a central role in the energy metabolism of eukaryotic cells and can influence cell death mechanisms, which are critical in tumorigenes...

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Bibliographic Details
Main Authors: Hu Qin, Aimitaji Abulaiti, Aierpati Maimaiti, Zulihuma Abulaiti, Guofeng Fan, Yirizhati Aili, Wenyu Ji, Zengliang Wang, Yongxin Wang
Format: Article
Language:English
Published: BMC 2023-09-01
Series:Journal of Translational Medicine
Subjects:
Machine learning
Precision oncology
Lower-grade glioma
Programmed cell death
Mitochondrial function
Online Access:https://doi.org/10.1186/s12967-023-04468-x

Internet

https://doi.org/10.1186/s12967-023-04468-x

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