Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

312 related articles for article (PubMed ID: 36463703)

  • 21. Development and validation of a multi-modality fusion deep learning model for differentiating glioblastoma from solitary brain metastases.
    Shen S; Li C; Fan Y; Lu S; Yan Z; Liu H; Zhou H; Zhang Z
    Zhong Nan Da Xue Xue Bao Yi Xue Ban; 2024 Jan; 49(1):58-67. PubMed ID: 38615167
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Radiomic Based Machine Learning Performance for a Three Class Problem in Neuro-Oncology: Time to Test the Waters?
    Priya S; Liu Y; Ward C; Le NH; Soni N; Pillenahalli Maheshwarappa R; Monga V; Zhang H; Sonka M; Bathla G
    Cancers (Basel); 2021 May; 13(11):. PubMed ID: 34073840
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Preoperative Prediction of Ki-67 Status in Breast Cancer with Multiparametric MRI Using Transfer Learning.
    Liu W; Cheng Y; Liu Z; Liu C; Cattell R; Xie X; Wang Y; Yang X; Ye W; Liang C; Li J; Gao Y; Huang C; Liang C
    Acad Radiol; 2021 Feb; 28(2):e44-e53. PubMed ID: 32278690
    [TBL] [Abstract][Full Text] [Related]  

  • 24. 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]  

  • 25. An MRI-based Radiomics Classifier for Preoperative Prediction of Ki-67 Status in Breast Cancer.
    Liang C; Cheng Z; Huang Y; He L; Chen X; Ma Z; Huang X; Liang C; Liu Z
    Acad Radiol; 2018 Sep; 25(9):1111-1117. PubMed ID: 29428211
    [TBL] [Abstract][Full Text] [Related]  

  • 26. 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]  

  • 27. Multiparametric imaging-based differentiation of lymphoma and glioblastoma: using T1-perfusion, diffusion, and susceptibility-weighted MRI.
    Saini J; Kumar Gupta P; Awasthi A; Pandey CM; Singh A; Patir R; Ahlawat S; Sadashiva N; Mahadevan A; Kumar Gupta R
    Clin Radiol; 2018 Nov; 73(11):986.e7-986.e15. PubMed ID: 30197047
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Handcrafted and Deep Learning-Based Radiomic Models Can Distinguish GBM from Brain Metastasis.
    Liu Z; Jiang Z; Meng L; Yang J; Liu Y; Zhang Y; Peng H; Li J; Xiao G; Zhang Z; Zhou R
    J Oncol; 2021; 2021():5518717. PubMed ID: 34188680
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures.
    Zhang Y; Zhang H; Zhang H; Ouyang Y; Su R; Yang W; Huang B
    J Magn Reson Imaging; 2023 Nov; ():. PubMed ID: 37955154
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Differentiating Glioblastoma Multiforme from Brain Metastases Using Multidimensional Radiomics Features Derived from MRI and Multiple Machine Learning Models.
    Bijari S; Jahanbakhshi A; Hajishafiezahramini P; Abdolmaleki P
    Biomed Res Int; 2022; 2022():2016006. PubMed ID: 36212721
    [TBL] [Abstract][Full Text] [Related]  

  • 31. A radiomics-based model to differentiate glioblastoma from solitary brain metastases.
    Su CQ; Chen XT; Duan SF; Zhang JX; You YP; Lu SS; Hong XN
    Clin Radiol; 2021 Aug; 76(8):629.e11-629.e18. PubMed ID: 34092362
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Radiomics-based differentiation between glioblastoma and primary central nervous system lymphoma: a comparison of diagnostic performance across different MRI sequences and machine learning techniques.
    Bathla G; Priya S; Liu Y; Ward C; Le NH; Soni N; Maheshwarappa RP; Monga V; Zhang H; Sonka M
    Eur Radiol; 2021 Nov; 31(11):8703-8713. PubMed ID: 33890149
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Quantification of Radiomics features of Peritumoral Vasogenic Edema extracted from fluid-attenuated inversion recovery images in glioblastoma and isolated brain metastasis, using T1-dynamic contrast-enhanced Perfusion analysis.
    Parvaze PS; Bhattacharjee R; Verma YK; Singh RK; Yadav V; Singh A; Khanna G; Ahlawat S; Trivedi R; Patir R; Vaishya S; Shah TJ; Gupta RK
    NMR Biomed; 2023 May; 36(5):e4884. PubMed ID: 36453877
    [TBL] [Abstract][Full Text] [Related]  

  • 34. 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]  

  • 35. High-order radiomics features based on T2 FLAIR MRI predict multiple glioma immunohistochemical features: A more precise and personalized gliomas management.
    Li J; Liu S; Qin Y; Zhang Y; Wang N; Liu H
    PLoS One; 2020; 15(1):e0227703. PubMed ID: 31968004
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Machine learning-based Radiomics analysis for differentiation degree and lymphatic node metastasis of extrahepatic cholangiocarcinoma.
    Tang Y; Yang CM; Su S; Wang WJ; Fan LP; Shu J
    BMC Cancer; 2021 Nov; 21(1):1268. PubMed ID: 34819043
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Radiomics Analysis Based on Magnetic Resonance Imaging for Preoperative Overall Survival Prediction in Isocitrate Dehydrogenase Wild-Type Glioblastoma.
    Wang S; Xiao F; Sun W; Yang C; Ma C; Huang Y; Xu D; Li L; Chen J; Li H; Xu H
    Front Neurosci; 2021; 15():791776. PubMed ID: 35153659
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Diffusion radiomics as a diagnostic model for atypical manifestation of primary central nervous system lymphoma: development and multicenter external validation.
    Kang D; Park JE; Kim YH; Kim JH; Oh JY; Kim J; Kim Y; Kim ST; Kim HS
    Neuro Oncol; 2018 Aug; 20(9):1251-1261. PubMed ID: 29438500
    [TBL] [Abstract][Full Text] [Related]  

  • 39. 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]  

  • 40. A radiomics-clinical nomogram for preoperative prediction of IDH1 mutation in primary glioblastoma multiforme.
    Su X; Sun H; Chen N; Roberts N; Yang X; Wang W; Li J; Huang X; Gong Q; Yue Q
    Clin Radiol; 2020 Dec; 75(12):963.e7-963.e15. PubMed ID: 32921406
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 16.