Metabolic detection of malignant brain gliomas through plasma lipidomic analysis and support vector machine-based machine learning
Summary: Background: Most malignant brain gliomas (MBGs) are associated with dismal outcomes, mainly due to their late diagnosis. Current diagnostic methods for MBGs are based on imaging and histological examination, which limits their early detection. Here, we aimed to identify reliable plasma lip...
Main Authors: | Juntuo Zhou, Nan Ji, Guangxi Wang, Yang Zhang, Huajie Song, Yuyao Yuan, Chunyuan Yang, Yan Jin, Zhe Zhang, Liwei Zhang, Yuxin Yin |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2022-07-01
|
Series: | EBioMedicine |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S235239642200278X |
Similar Items
-
Metabolomic and Lipidomic Profiling of Gliomas—A New Direction in Personalized Therapies
by: Magdalena Gaca-Tabaszewska, et al.
Published: (2022-10-01) -
Metabolic Alterations Related to Glioma Grading Based on Metabolomics and Lipidomics Analyses
by: Di Yu, et al.
Published: (2020-11-01) -
Treatment of Malignant Gliomas by Therapies Against Matrix Metalloproteinases
by: Charles Matouk, et al.
Published: (2020-12-01) -
Analysis of MRI Images of the Liver, using a Combination of Wavelet and Principle Component Analysis (Pca) and Support Vector Machine (SVM) for the Diagnosis and Classification of Benign and Malignant Tumors
by: Bahman Cheraghi Gharakhanloo, et al.
Published: (2018-04-01) -
Surgical Management of Malignant Glioma in the Elderly
by: Julia Klingenschmid, et al.
Published: (2022-05-01)