These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

135 related articles for article (PubMed ID: 35396525)

  • 21. Radiomics signature: A potential biomarker for the prediction of MGMT promoter methylation in glioblastoma.
    Xi YB; Guo F; Xu ZL; Li C; Wei W; Tian P; Liu TT; Liu L; Chen G; Ye J; Cheng G; Cui LB; Zhang HJ; Qin W; Yin H
    J Magn Reson Imaging; 2018 May; 47(5):1380-1387. PubMed ID: 28926163
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Developing and validating a deep learning and radiomic model for glioma grading using multiplanar reconstructed magnetic resonance contrast-enhanced T1-weighted imaging: a robust, multi-institutional study.
    Ding J; Zhao R; Qiu Q; Chen J; Duan J; Cao X; Yin Y
    Quant Imaging Med Surg; 2022 Feb; 12(2):1517-1528. PubMed ID: 35111644
    [TBL] [Abstract][Full Text] [Related]  

  • 23. 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]  

  • 24. 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]  

  • 25. 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]  

  • 26. Radiomics-based machine learning methods for isocitrate dehydrogenase genotype prediction of diffuse gliomas.
    Wu S; Meng J; Yu Q; Li P; Fu S
    J Cancer Res Clin Oncol; 2019 Mar; 145(3):543-550. PubMed ID: 30719536
    [TBL] [Abstract][Full Text] [Related]  

  • 27. 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]  

  • 28. MRI features predict p53 status in lower-grade gliomas via a machine-learning approach.
    Li Y; Qian Z; Xu K; Wang K; Fan X; Li S; Jiang T; Liu X; Wang Y
    Neuroimage Clin; 2018; 17():306-311. PubMed ID: 29527478
    [TBL] [Abstract][Full Text] [Related]  

  • 29. 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]  

  • 30. 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]  

  • 31. Prediction of pseudoprogression and long-term outcome of vestibular schwannoma after Gamma Knife radiosurgery based on preradiosurgical MR radiomics.
    Yang HC; Wu CC; Lee CC; Huang HE; Lee WK; Chung WY; Wu HM; Guo WY; Wu YT; Lu CF
    Radiother Oncol; 2021 Feb; 155():123-130. PubMed ID: 33161011
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Predicting the Grade of Prostate Cancer Based on a Biparametric MRI Radiomics Signature.
    Zhang L; Zhe X; Tang M; Zhang J; Ren J; Zhang X; Li L
    Contrast Media Mol Imaging; 2021; 2021():7830909. PubMed ID: 35024015
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Feasibility on the Use of Radiomics Features of 11[C]-MET PET/CT in Central Nervous System Tumours: Preliminary Results on Potential Grading Discrimination Using a Machine Learning Model.
    Russo G; Stefano A; Alongi P; Comelli A; Catalfamo B; Mantarro C; Longo C; Altieri R; Certo F; Cosentino S; Sabini MG; Richiusa S; Barbagallo GMV; Ippolito M
    Curr Oncol; 2021 Dec; 28(6):5318-5331. PubMed ID: 34940083
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Standardization of brain MR images across machines and protocols: bridging the gap for MRI-based radiomics.
    Carré A; Klausner G; Edjlali M; Lerousseau M; Briend-Diop J; Sun R; Ammari S; Reuzé S; Alvarez Andres E; Estienne T; Niyoteka S; Battistella E; Vakalopoulou M; Dhermain F; Paragios N; Deutsch E; Oppenheim C; Pallud J; Robert C
    Sci Rep; 2020 Jul; 10(1):12340. PubMed ID: 32704007
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Incorporating diffusion- and perfusion-weighted MRI into a radiomics model improves diagnostic performance for pseudoprogression in glioblastoma patients.
    Kim JY; Park JE; Jo Y; Shim WH; Nam SJ; Kim JH; Yoo RE; Choi SH; Kim HS
    Neuro Oncol; 2019 Feb; 21(3):404-414. PubMed ID: 30107606
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Prediction of H3K27M-mutant brainstem glioma by amide proton transfer-weighted imaging and its derived radiomics.
    Zhuo Z; Qu L; Zhang P; Duan Y; Cheng D; Xu X; Sun T; Ding J; Xie C; Liu X; Haller S; Barkhof F; Zhang L; Liu Y
    Eur J Nucl Med Mol Imaging; 2021 Dec; 48(13):4426-4436. PubMed ID: 34131804
    [TBL] [Abstract][Full Text] [Related]  

  • 37. MRI-based delta-radiomics predicts pathologic complete response in high-grade soft-tissue sarcoma patients treated with neoadjuvant therapy.
    Peeken JC; Asadpour R; Specht K; Chen EY; Klymenko O; Akinkuoroye V; Hippe DS; Spraker MB; Schaub SK; Dapper H; Knebel C; Mayr NA; Gersing AS; Woodruff HC; Lambin P; Nyflot MJ; Combs SE
    Radiother Oncol; 2021 Nov; 164():73-82. PubMed ID: 34506832
    [TBL] [Abstract][Full Text] [Related]  

  • 38. A radiomic signature as a non-invasive predictor of progression-free survival in patients with lower-grade gliomas.
    Liu X; Li Y; Qian Z; Sun Z; Xu K; Wang K; Liu S; Fan X; Li S; Zhang Z; Jiang T; Wang Y
    Neuroimage Clin; 2018; 20():1070-1077. PubMed ID: 30366279
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Better efficacy in differentiating WHO grade II from III oligodendrogliomas with machine-learning than radiologist's reading from conventional T1 contrast-enhanced and fluid attenuated inversion recovery images.
    Zhao SS; Feng XL; Hu YC; Han Y; Tian Q; Sun YZ; Zhang J; Ge XW; Cheng SC; Li XL; Mao L; Shen SN; Yan LF; Cui GB; Wang W
    BMC Neurol; 2020 Feb; 20(1):48. PubMed ID: 32033580
    [TBL] [Abstract][Full Text] [Related]  

  • 40. The Nomogram of MRI-based Radiomics with Complementary Visual Features by Machine Learning Improves Stratification of Glioblastoma Patients: A Multicenter Study.
    Xu Y; He X; Li Y; Pang P; Shu Z; Gong X
    J Magn Reson Imaging; 2021 Aug; 54(2):571-583. PubMed ID: 33559302
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.