BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

236 related articles for article (PubMed ID: 35652509)

  • 1. Radiomic-Based MRI for Classification of Solitary Brain Metastases Subtypes From Primary Lymphoma of the Central Nervous System.
    Zhao LM; Hu R; Xie FF; Clay Kargilis D; Imami M; Yang S; Guo JQ; Jiao X; Chen RT; Wei-Hua L; Li L
    J Magn Reson Imaging; 2023 Jan; 57(1):227-235. PubMed ID: 35652509
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Machine learning based on multi-parametric magnetic resonance imaging to differentiate glioblastoma multiforme from primary cerebral nervous system lymphoma.
    Nakagawa M; Nakaura T; Namimoto T; Kitajima M; Uetani H; Tateishi M; Oda S; Utsunomiya D; Makino K; Nakamura H; Mukasa A; Hirai T; Yamashita Y
    Eur J Radiol; 2018 Nov; 108():147-154. PubMed ID: 30396648
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Deep Learning With an Attention Mechanism for Differentiating the Origin of Brain Metastasis Using MR images.
    Jiao T; Li F; Cui Y; Wang X; Li B; Shi F; Xia Y; Zhou Q; Zeng Q
    J Magn Reson Imaging; 2023 Nov; 58(5):1624-1635. PubMed ID: 36965182
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep Learning for Automatic Differential Diagnosis of Primary Central Nervous System Lymphoma and Glioblastoma: Multi-Parametric Magnetic Resonance Imaging Based Convolutional Neural Network Model.
    Xia W; Hu B; Li H; Shi W; Tang Y; Yu Y; Geng C; Wu Q; Yang L; Yu Z; Geng D; Li Y
    J Magn Reson Imaging; 2021 Sep; 54(3):880-887. PubMed ID: 33694250
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Primary central nervous system lymphoma and atypical glioblastoma: Differentiation using radiomics approach.
    Suh HB; Choi YS; Bae S; Ahn SS; Chang JH; Kang SG; Kim EH; Kim SH; Lee SK
    Eur Radiol; 2018 Sep; 28(9):3832-3839. PubMed ID: 29626238
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Detecting Double Expression Status in Primary Central Nervous System Lymphoma Using Multiparametric MRI Based Machine Learning.
    Liu G; Zhang X; Zhang N; Xiao H; Chen X; Ma L
    J Magn Reson Imaging; 2024 Jan; 59(1):231-239. PubMed ID: 37199225
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Multiparametric-MRI-Based Radiomics Model for Differentiating Primary Central Nervous System Lymphoma From Glioblastoma: Development and Cross-Vendor Validation.
    Xia W; Hu B; Li H; Geng C; Wu Q; Yang L; Yin B; Gao X; Li Y; Geng D
    J Magn Reson Imaging; 2021 Jan; 53(1):242-250. PubMed ID: 32864825
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Improving the Classification of PCNSL and Brain Metastases by Developing a Machine Learning Model Based on
    Cui C; Yao X; Xu L; Chao Y; Hu Y; Zhao S; Hu Y; Zhang J
    J Pers Med; 2023 Mar; 13(3):. PubMed ID: 36983721
    [No Abstract]   [Full Text] [Related]  

  • 9. Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomic Model for Discrimination of Pathological Subtypes of Craniopharyngioma.
    Huang ZS; Xiao X; Li XD; Mo HZ; He WL; Deng YH; Lu LJ; Wu YK; Liu H
    J Magn Reson Imaging; 2021 Nov; 54(5):1541-1550. PubMed ID: 34085336
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Radiomics features to distinguish glioblastoma from primary central nervous system lymphoma on multi-parametric MRI.
    Kim Y; Cho HH; Kim ST; Park H; Nam D; Kong DS
    Neuroradiology; 2018 Dec; 60(12):1297-1305. PubMed ID: 30232517
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A Triple-Classification Radiomics Model for the Differentiation of Primary Chordoma, Giant Cell Tumor, and Metastatic Tumor of Sacrum Based on T2-Weighted and Contrast-Enhanced T1-Weighted MRI.
    Yin P; Mao N; Zhao C; Wu J; Chen L; Hong N
    J Magn Reson Imaging; 2019 Mar; 49(3):752-759. PubMed ID: 30430686
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Radiomics analysis of T1WI and T2WI magnetic resonance images to differentiate between IgG4-related ophthalmic disease and orbital MALT lymphoma.
    Shao Y; Chen Y; Chen S; Wei R
    BMC Ophthalmol; 2023 Jun; 23(1):288. PubMed ID: 37353736
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Machine Learning-based Texture Analysis of Contrast-enhanced MR Imaging to Differentiate between Glioblastoma and Primary Central Nervous System Lymphoma.
    Kunimatsu A; Kunimatsu N; Yasaka K; Akai H; Kamiya K; Watadani T; Mori H; Abe O
    Magn Reson Med Sci; 2019 Jan; 18(1):44-52. PubMed ID: 29769456
    [TBL] [Abstract][Full Text] [Related]  

  • 14. An integrative non-invasive malignant brain tumors classification and Ki-67 labeling index prediction pipeline with radiomics approach.
    Zhang L; Liu X; Xu X; Liu W; Jia Y; Chen W; Fu X; Li Q; Sun X; Zhang Y; Shu S; Zhang X; Xiang R; Chen H; Sun P; Geng D; Yu Z; Liu J; Wang J
    Eur J Radiol; 2023 Jan; 158():110639. PubMed ID: 36463703
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Differentiation between glioblastoma, brain metastasis and subtypes using radiomics analysis.
    Artzi M; Bressler I; Ben Bashat D
    J Magn Reson Imaging; 2019 Aug; 50(2):519-528. PubMed ID: 30635952
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Role of intra-tumoral vasculature imaging features on susceptibility weighted imaging in differentiating primary central nervous system lymphoma from glioblastoma: a multiparametric comparison with pathological validation.
    Bhattacharjee R; Gupta M; Singh T; Sharma S; Khanna G; Parvaze SP; Patir R; Vaishya S; Ahlawat S; Singh A; Gupta RK
    Neuroradiology; 2022 Sep; 64(9):1801-1818. PubMed ID: 35435463
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Preoperative MRI-Based Radiomic Machine-Learning Nomogram May Accurately Distinguish Between Benign and Malignant Soft-Tissue Lesions: A Two-Center Study.
    Wang H; Zhang J; Bao S; Liu J; Hou F; Huang Y; Chen H; Duan S; Hao D; Liu J
    J Magn Reson Imaging; 2020 Sep; 52(3):873-882. PubMed ID: 32112598
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Differentiation between cerebral alveolar echinococcosis and brain metastases with radiomics combined machine learning approach.
    Yimit Y; Yasin P; Tuersun A; Abulizi A; Jia W; Wang Y; Nijiati M
    Eur J Med Res; 2023 Dec; 28(1):577. PubMed ID: 38071384
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Differentiation of Sinonasal NKT From Diffuse Large B-Cell Lymphoma Using Machine Learning and MRI-Based Radiomics.
    Zhang Y; Lin N; Xiao H; Xin E; Sha Y
    J Comput Assist Tomogr; 2023 Nov-Dec 01; 47(6):973-981. PubMed ID: 37948374
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Fully automated radiomics-based machine learning models for multiclass classification of single brain tumors: Glioblastoma, lymphoma, and metastasis.
    Joo B; Ahn SS; An C; Han K; Choi D; Kim H; Park JE; Kim HS; Lee SK
    J Neuroradiol; 2023 Jun; 50(4):388-395. PubMed ID: 36370829
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.