BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

147 related articles for article (PubMed ID: 38154107)

  • 1. 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]  

  • 2. 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]  

  • 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. 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]  

  • 5. 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]  

  • 6. 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]  

  • 7. [High-throughput texture analysis in the distinction of single metastatic brain tumors from high-grade gliomas].
    Yin HL; Li DB; Jiang Y; Li SH; Chen Y; Lin GW
    Zhonghua Zhong Liu Za Zhi; 2018 Nov; 40(11):841-846. PubMed ID: 30481936
    [No Abstract]   [Full Text] [Related]  

  • 8. On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI images.
    Sengupta A; Agarwal S; Gupta PK; Ahlawat S; Patir R; Gupta RK; Singh A
    Eur J Radiol; 2018 Sep; 106():199-208. PubMed ID: 30150045
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Genotype prediction of ATRX mutation in lower-grade gliomas using an MRI radiomics signature.
    Li Y; Liu X; Qian Z; Sun Z; Xu K; Wang K; Fan X; Zhang Z; Li S; Wang Y; Jiang T
    Eur Radiol; 2018 Jul; 28(7):2960-2968. PubMed ID: 29404769
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. 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]  

  • 13. Imaging biomarker analysis of advanced multiparametric MRI for glioma grading.
    Vamvakas A; Williams SC; Theodorou K; Kapsalaki E; Fountas K; Kappas C; Vassiou K; Tsougos I
    Phys Med; 2019 Apr; 60():188-198. PubMed ID: 30910431
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Fusion Radiomics Features from Conventional MRI Predict MGMT Promoter Methylation Status in Lower Grade Gliomas.
    Jiang C; Kong Z; Liu S; Feng S; Zhang Y; Zhu R; Chen W; Wang Y; Lyu Y; You H; Zhao D; Wang R; Wang Y; Ma W; Feng F
    Eur J Radiol; 2019 Dec; 121():108714. PubMed ID: 31704598
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Noninvasive IDH1 mutation estimation based on a quantitative radiomics approach for grade II glioma.
    Yu J; Shi Z; Lian Y; Li Z; Liu T; Gao Y; Wang Y; Chen L; Mao Y
    Eur Radiol; 2017 Aug; 27(8):3509-3522. PubMed ID: 28004160
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A machine learning-based survival prediction model of high grade glioma by integration of clinical and dose-volume histogram parameters.
    Chen H; Li C; Zheng L; Lu W; Li Y; Wei Q
    Cancer Med; 2021 Apr; 10(8):2774-2786. PubMed ID: 33760360
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Diffusion- and perfusion-weighted MRI radiomics model may predict isocitrate dehydrogenase (IDH) mutation and tumor aggressiveness in diffuse lower grade glioma.
    Kim M; Jung SY; Park JE; Jo Y; Park SY; Nam SJ; Kim JH; Kim HS
    Eur Radiol; 2020 Apr; 30(4):2142-2151. PubMed ID: 31828414
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Non-invasive genotype prediction of chromosome 1p/19q co-deletion by development and validation of an MRI-based radiomics signature in lower-grade gliomas.
    Han Y; Xie Z; Zang Y; Zhang S; Gu D; Zhou M; Gevaert O; Wei J; Li C; Chen H; Du J; Liu Z; Dong D; Tian J; Zhou D
    J Neurooncol; 2018 Nov; 140(2):297-306. PubMed ID: 30097822
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Radiomics-Based Machine Learning Classification for Glioma Grading Using Diffusion- and Perfusion-Weighted Magnetic Resonance Imaging.
    Hashido T; Saito S; Ishida T
    J Comput Assist Tomogr; 2021 Jul-Aug 01; 45(4):606-613. PubMed ID: 34270479
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Radiomics Nomogram Building From Multiparametric MRI to Predict Grade in Patients With Glioma: A Cohort Study.
    Wang Q; Li Q; Mi R; Ye H; Zhang H; Chen B; Li Y; Huang G; Xia J
    J Magn Reson Imaging; 2019 Mar; 49(3):825-833. PubMed ID: 30260592
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.