138 related articles for article (PubMed ID: 37095939)
1. Application of colony-stimulating factor 3 in determining the prognosis of high-grade gliomas based on magnetic resonance imaging radiomics.
Li L; Hou M; Fang S
Heliyon; 2023 Apr; 9(4):e15325. PubMed ID: 37095939
[TBL] [Abstract][Full Text] [Related]
2. MRI-based Machine Learning Radiomics Can Predict CSF1R Expression Level and Prognosis in High-grade Gliomas.
Lai Y; Wu Y; Chen X; Gu W; Zhou G; Weng M
J Imaging Inform Med; 2024 Feb; 37(1):209-229. PubMed ID: 38343263
[TBL] [Abstract][Full Text] [Related]
3. Radiomics Features on Magnetic Resonance Images Can Predict C5aR1 Expression Levels and Prognosis in High-Grade Glioma.
Wu Z; Yang Y; Zha Y
Cancers (Basel); 2023 Sep; 15(18):. PubMed ID: 37760630
[TBL] [Abstract][Full Text] [Related]
4. Integrated analysis reveals the potential of cluster of differentiation 86 as a key biomarker in high-grade glioma.
Wen X; Wang C; Pan Z; Jin Y; Wang H; Zhou J; Sun C; Ye G; Chen M
Aging (Albany NY); 2023 Dec; 15(24):15402-15418. PubMed ID: 38154107
[TBL] [Abstract][Full Text] [Related]
5. Improving survival prediction of high-grade glioma via machine learning techniques based on MRI radiomic, genetic and clinical risk factors.
Tan Y; Mu W; Wang XC; Yang GQ; Gillies RJ; Zhang H
Eur J Radiol; 2019 Nov; 120():108609. PubMed ID: 31606714
[TBL] [Abstract][Full Text] [Related]
6. Radiomic Prediction of CCND1 Expression Levels and Prognosis in Low-grade Glioma Based on Magnetic Resonance Imaging.
Zhao K; Zhang H; Lin J; Xu S; Liu J; Qian X; Gu Y; Ren G; Lu X; Chen B; Chen D; Yan J; Ma J; Wei W; Wang Y
Acad Radiol; 2024 May; ():. PubMed ID: 38824087
[TBL] [Abstract][Full Text] [Related]
7. BTK Expression Level Prediction and the High-Grade Glioma Prognosis Using Radiomic Machine Learning Models.
Jiang C; Sun C; Wang X; Ma S; Jia W; Zhang D
J Imaging Inform Med; 2024 Feb; ():. PubMed ID: 38381384
[TBL] [Abstract][Full Text] [Related]
8. MRI-derived radiomics assessing tumor-infiltrating macrophages enable prediction of immune-phenotype, immunotherapy response and survival in glioma.
Chen D; Zhang R; Huang X; Ji C; Xia W; Qi Y; Yang X; Lin L; Wang J; Cheng H; Tang W; Yu J; Hoon DSB; Zhang J; Gao X; Yao Y
Biomark Res; 2024 Jan; 12(1):14. PubMed ID: 38291499
[TBL] [Abstract][Full Text] [Related]
9. Predictive value of magnetic resonance imaging radiomics-based machine learning for disease progression in patients with high-grade glioma.
Li Z; Chen L; Song Y; Dai G; Duan L; Luo Y; Wang G; Xiao Q; Li G; Bai S
Quant Imaging Med Surg; 2023 Jan; 13(1):224-236. PubMed ID: 36620140
[TBL] [Abstract][Full Text] [Related]
10. Computed tomography-based radiomics prediction of CTLA4 expression and prognosis in clear cell renal cell carcinoma.
He H; Jin Z; Dai J; Wang H; Sun J; Xu D
Cancer Med; 2023 Mar; 12(6):7627-7638. PubMed ID: 36397666
[TBL] [Abstract][Full Text] [Related]
11. Magnetic resonance imaging-based radiomics was used to evaluate the level of prognosis-related immune cell infiltration in breast cancer tumor microenvironment.
Qian H; Ren X; Xu M; Fang Z; Zhang R; Bu Y; Zhou C
BMC Med Imaging; 2024 Feb; 24(1):31. PubMed ID: 38308230
[TBL] [Abstract][Full Text] [Related]
12. Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas.
Park CJ; Han K; Kim H; Ahn SS; Choi YS; Park YW; Chang JH; Kim SH; Jain R; Lee SK
Eur Radiol; 2020 Dec; 30(12):6464-6474. PubMed ID: 32740813
[TBL] [Abstract][Full Text] [Related]
13. Development of a nomograph integrating radiomics and deep features based on MRI to predict the prognosis of high grade Gliomas.
Wang Y; Shao Q; Luo S; Fu R
Math Biosci Eng; 2021 Sep; 18(6):8084-8095. PubMed ID: 34814290
[TBL] [Abstract][Full Text] [Related]
14. Association between small heat shock protein B11 and the prognostic value of MGMT promoter methylation in patients with high-grade glioma.
Cheng W; Li M; Jiang Y; Zhang C; Cai J; Wang K; Wu A
J Neurosurg; 2016 Jul; 125(1):7-16. PubMed ID: 26544773
[TBL] [Abstract][Full Text] [Related]
15. Radiomics Profiling Identifies the Incremental Value of MRI Features beyond Key Molecular Biomarkers for the Risk Stratification of High-Grade Gliomas.
Yang G; Sha Y; Wang X; Tan Y; Zhang H
Contrast Media Mol Imaging; 2022; 2022():8952357. PubMed ID: 35386727
[TBL] [Abstract][Full Text] [Related]
16. Radiomics strategy for glioma grading using texture features from multiparametric MRI.
Tian Q; Yan LF; Zhang X; Zhang X; Hu YC; Han Y; Liu ZC; Nan HY; Sun Q; Sun YZ; Yang Y; Yu Y; Zhang J; Hu B; Xiao G; Chen P; Tian S; Xu J; Wang W; Cui GB
J Magn Reson Imaging; 2018 Dec; 48(6):1518-1528. PubMed ID: 29573085
[TBL] [Abstract][Full Text] [Related]
17. Using radiomics based on multicenter magnetic resonance images to predict isocitrate dehydrogenase mutation status of gliomas.
Liu Y; Zheng Z; Wang Z; Qian X; Yao Z; Cheng C; Zhou Z; Gao F; Dai Y
Quant Imaging Med Surg; 2023 Apr; 13(4):2143-2155. PubMed ID: 37064376
[TBL] [Abstract][Full Text] [Related]
18. Noninvasive Prediction of TERT Promoter Mutations in High-Grade Glioma by Radiomics Analysis Based on Multiparameter MRI.
Tian H; Wu H; Wu G; Xu G
Biomed Res Int; 2020; 2020():3872314. PubMed ID: 32509858
[TBL] [Abstract][Full Text] [Related]
19. Machine learning and radiomic phenotyping of lower grade gliomas: improving survival prediction.
Choi YS; Ahn SS; Chang JH; Kang SG; Kim EH; Kim SH; Jain R; Lee SK
Eur Radiol; 2020 Jul; 30(7):3834-3842. PubMed ID: 32162004
[TBL] [Abstract][Full Text] [Related]
20. Radiomics-based MRI for predicting Erythropoietin-producing hepatocellular receptor A2 expression and tumor grade in brain diffuse gliomas.
Liu X; Li J; Liao X; Luo Z; Xu Q; Pan H; Zhou Q; Tao Y; Shi F; Lu G; Zhang Z
Neuroradiology; 2022 Feb; 64(2):323-331. PubMed ID: 34368897
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
