309 related articles for article (PubMed ID: 36463703)
21. 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]
22. 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]
23. 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]
24. 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]
25. 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]
26. 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]
27. 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]
28. 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]
29. 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]
30. 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]
31. 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]
32. 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]
33. 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]
34. 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]
35. 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]
36. 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]
37. 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]
38. 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]
39. Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.
Huang Y; Wei L; Hu Y; Shao N; Lin Y; He S; Shi H; Zhang X; Lin Y
Front Oncol; 2021; 11():706733. PubMed ID: 34490107
[TBL] [Abstract][Full Text] [Related]
40. Multi-parametric MRI-based radiomics signature for preoperative prediction of Ki-67 proliferation status in sinonasal malignancies: a two-centre study.
Bi S; Li J; Wang T; Man F; Zhang P; Hou F; Wang H; Hao D
Eur Radiol; 2022 Oct; 32(10):6933-6942. PubMed ID: 35687135
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
