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 *

297 related articles for article (PubMed ID: 37373909)

  • 1. Machine-Learning-Based Radiomics for Classifying Glioma Grade from Magnetic Resonance Images of the Brain.
    Kumar A; Jha AK; Agarwal JP; Yadav M; Badhe S; Sahay A; Epari S; Sahu A; Bhattacharya K; Chatterjee A; Ganeshan B; Rangarajan V; Moyiadi A; Gupta T; Goda JS
    J Pers Med; 2023 May; 13(6):. PubMed ID: 37373909
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Classification of the glioma grading using radiomics analysis.
    Cho HH; Lee SH; Kim J; Park H
    PeerJ; 2018; 6():e5982. PubMed ID: 30498643
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Predicting Histopathological Grading of Adult Gliomas Based On Preoperative Conventional Multimodal MRI Radiomics: A Machine Learning Model.
    Du P; Liu X; Wu X; Chen J; Cao A; Geng D
    Brain Sci; 2023 Jun; 13(6):. PubMed ID: 37371390
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Predicting IDH subtype of grade 4 astrocytoma and glioblastoma from tumor radiomic patterns extracted from multiparametric magnetic resonance images using a machine learning approach.
    Kandalgaonkar P; Sahu A; Saju AC; Joshi A; Mahajan A; Thakur M; Sahay A; Epari S; Sinha S; Dasgupta A; Chatterjee A; Shetty P; Moiyadi A; Agarwal J; Gupta T; Goda JS
    Front Oncol; 2022; 12():879376. PubMed ID: 36276136
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Glioma Tumor Grading Using Radiomics on Conventional MRI: A Comparative Study of WHO 2021 and WHO 2016 Classification of Central Nervous Tumors.
    Moodi F; Khodadadi Shoushtari F; Ghadimi DJ; Valizadeh G; Khormali E; Salari HM; Ohadi MAD; Nilipour Y; Jahanbakhshi A; Rad HS
    J Magn Reson Imaging; 2024 Sep; 60(3):923-938. PubMed ID: 38031466
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Radiomics MRI Phenotyping with Machine Learning to Predict the Grade of Lower-Grade Gliomas: A Study Focused on Nonenhancing Tumors.
    Park YW; Choi YS; Ahn SS; Chang JH; Kim SH; Lee SK
    Korean J Radiol; 2019 Sep; 20(9):1381-1389. PubMed ID: 31464116
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Radiogenomics of lower-grade gliomas: machine learning-based MRI texture analysis for predicting 1p/19q codeletion status.
    Kocak B; Durmaz ES; Ates E; Sel I; Turgut Gunes S; Kaya OK; Zeynalova A; Kilickesmez O
    Eur Radiol; 2020 Feb; 30(2):877-886. PubMed ID: 31691122
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. 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]  

  • 12. Machine learning predicts histologic type and grade of canine gliomas based on MRI texture analysis.
    Barge P; Oevermann A; Maiolini A; Durand A
    Vet Radiol Ultrasound; 2023 Jul; 64(4):724-732. PubMed ID: 37133981
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading.
    Inano R; Oishi N; Kunieda T; Arakawa Y; Yamao Y; Shibata S; Kikuchi T; Fukuyama H; Miyamoto S
    Neuroimage Clin; 2014; 5():396-407. PubMed ID: 25180159
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Glioma grading prediction using multiparametric magnetic resonance imaging-based radiomics combined with proton magnetic resonance spectroscopy and diffusion tensor imaging.
    Lin K; Cidan W; Qi Y; Wang X
    Med Phys; 2022 Jul; 49(7):4419-4429. PubMed ID: 35366379
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predicting histological grade in pediatric glioma using multiparametric radiomics and conventional MRI features.
    Zhou T; Qiao B; Peng B; Liu Y; Gong Z; Kang M; He Y; Pang C; Dai Y; Sheng M
    Sci Rep; 2024 Jun; 14(1):13683. PubMed ID: 38871755
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Machine-Learning and Radiomics-Based Preoperative Prediction of Ki-67 Expression in Glioma Using MRI Data.
    Ni J; Zhang H; Yang Q; Fan X; Xu J; Sun J; Zhang J; Hu Y; Xiao Z; Zhao Y; Zhu H; Shi X; Feng W; Wang J; Wan C; Zhang X; Liu Y; You Y; Yu Y
    Acad Radiol; 2024 Aug; 31(8):3397-3405. PubMed ID: 38458887
    [TBL] [Abstract][Full Text] [Related]  

  • 17. An investigation of machine learning methods in delta-radiomics feature analysis.
    Chang Y; Lafata K; Sun W; Wang C; Chang Z; Kirkpatrick JP; Yin FF
    PLoS One; 2019; 14(12):e0226348. PubMed ID: 31834910
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Predicting Isocitrate Dehydrogenase (IDH) Mutation Status in Gliomas Using Multiparameter MRI Radiomics Features.
    Peng H; Huo J; Li B; Cui Y; Zhang H; Zhang L; Ma L
    J Magn Reson Imaging; 2021 May; 53(5):1399-1407. PubMed ID: 33179832
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Machine learning assisted DSC-MRI radiomics as a tool for glioma classification by grade and mutation status.
    Sudre CH; Panovska-Griffiths J; Sanverdi E; Brandner S; Katsaros VK; Stranjalis G; Pizzini FB; Ghimenton C; Surlan-Popovic K; Avsenik J; Spampinato MV; Nigro M; Chatterjee AR; Attye A; Grand S; Krainik A; Anzalone N; Conte GM; Romeo V; Ugga L; Elefante A; Ciceri EF; Guadagno E; Kapsalaki E; Roettger D; Gonzalez J; Boutelier T; Cardoso MJ; Bisdas S
    BMC Med Inform Decis Mak; 2020 Jul; 20(1):149. PubMed ID: 32631306
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.