118 related articles for article (PubMed ID: 37380154)
1. Oligodendrocyte Transcription Factor 2 as a Potential Prognostic Biomarker of Glioblastoma: Kaplan-Meier Analysis and the Development of a Binary Predictive Model Based on Visually Accessible Rembrandt Image and Magnetic Resonance Imaging Radiomic Features.
Mei N; Lu Y; Yang S; Jiang S; Ruan Z; Wang D; Liu X; Ying Y; Li X; Yin B
J Comput Assist Tomogr; 2023 Jul-Aug 01; 47(4):650-658. PubMed ID: 37380154
[TBL] [Abstract][Full Text] [Related]
2. Machine learning-based radiomic, clinical and semantic feature analysis for predicting overall survival and MGMT promoter methylation status in patients with glioblastoma.
Lu Y; Patel M; Natarajan K; Ughratdar I; Sanghera P; Jena R; Watts C; Sawlani V
Magn Reson Imaging; 2020 Dec; 74():161-170. PubMed ID: 32980505
[TBL] [Abstract][Full Text] [Related]
3. Analysis of heterogeneity of peritumoral T2 hyperintensity in patients with pretreatment glioblastoma: Prognostic value of MRI-based radiomics.
Choi Y; Ahn KJ; Nam Y; Jang J; Shin NY; Choi HS; Jung SL; Kim BS
Eur J Radiol; 2019 Nov; 120():108642. PubMed ID: 31546124
[TBL] [Abstract][Full Text] [Related]
4. MRI Features May Predict Molecular Features of Glioblastoma in
Park CJ; Han K; Kim H; Ahn SS; Choi D; Park YW; Chang JH; Kim SH; Cha S; Lee SK
AJNR Am J Neuroradiol; 2021 Mar; 42(3):448-456. PubMed ID: 33509914
[TBL] [Abstract][Full Text] [Related]
5. Dynamic Contrast-Enhanced T1-Weighted Perfusion Magnetic Resonance Imaging Identifies Glioblastoma Immunohistochemical Biomarkers via Tumoral and Peritumoral Approach: A Pilot Study.
Ozturk K; Soylu E; Tolunay S; Narter S; Hakyemez B
World Neurosurg; 2019 Aug; 128():e195-e208. PubMed ID: 31003026
[TBL] [Abstract][Full Text] [Related]
6. Combination of pre-treatment dynamic [
Li Z; Holzgreve A; Unterrainer LM; Ruf VC; Quach S; Bartos LM; Suchorska B; Niyazi M; Wenter V; Herms J; Bartenstein P; Tonn JC; Unterrainer M; Albert NL; Kaiser L
Eur J Nucl Med Mol Imaging; 2023 Jan; 50(2):535-545. PubMed ID: 36227357
[TBL] [Abstract][Full Text] [Related]
7. A Comparative and Summative Study of Radiomics-based Overall Survival Prediction in Glioblastoma Patients.
Ruan Z; Mei N; Lu Y; Xiong J; Li X; Zheng W; Liu L; Yin B
J Comput Assist Tomogr; 2022 May-Jun 01; 46(3):470-479. PubMed ID: 35405713
[TBL] [Abstract][Full Text] [Related]
8. Biological underpinnings of radiomic magnetic resonance imaging phenotypes for risk stratification in IDH wild-type glioblastoma.
Guan F; Wang Z; Qiu Y; Guo Y; Pei D; Wang M; Xing A; Liu Z; Yu B; Cheng J; Liu X; Ji Y; Yan D; Yan J; Zhang Z
J Transl Med; 2023 Nov; 21(1):841. PubMed ID: 37993907
[TBL] [Abstract][Full Text] [Related]
9. Semantic imaging features predict disease progression and survival in glioblastoma multiforme patients.
Peeken JC; Hesse J; Haller B; Kessel KA; Nüsslin F; Combs SE
Strahlenther Onkol; 2018 Jun; 194(6):580-590. PubMed ID: 29442128
[TBL] [Abstract][Full Text] [Related]
10. Radiomic Analysis Reveals Prognostic Information in T1-Weighted Baseline Magnetic Resonance Imaging in Patients With Glioblastoma.
Ingrisch M; Schneider MJ; Nörenberg D; Negrao de Figueiredo G; Maier-Hein K; Suchorska B; Schüller U; Albert N; Brückmann H; Reiser M; Tonn JC; Ertl-Wagner B
Invest Radiol; 2017 Jun; 52(6):360-366. PubMed ID: 28079702
[TBL] [Abstract][Full Text] [Related]
11. OLIG2 expression level could be used as an independent prognostic factor for patients with cerebellar Glioblastoma (cGBM).
Zhou J; Shi LF; Wang Z; Li M; Zhang JS; Mao Y; Hua W
Clinics (Sao Paulo); 2023; 78():100120. PubMed ID: 37001387
[TBL] [Abstract][Full Text] [Related]
12. Machine learning-based radiomic evaluation of treatment response prediction in glioblastoma.
Patel M; Zhan J; Natarajan K; Flintham R; Davies N; Sanghera P; Grist J; Duddalwar V; Peet A; Sawlani V
Clin Radiol; 2021 Aug; 76(8):628.e17-628.e27. PubMed ID: 33941364
[TBL] [Abstract][Full Text] [Related]
13. Radiogenomic analysis of PTEN mutation in glioblastoma using preoperative multi-parametric magnetic resonance imaging.
Li Y; Liang Y; Sun Z; Xu K; Fan X; Li S; Zhang Z; Jiang T; Liu X; Wang Y
Neuroradiology; 2019 Nov; 61(11):1229-1237. PubMed ID: 31218383
[TBL] [Abstract][Full Text] [Related]
14. Prediction of survival with multi-scale radiomic analysis in glioblastoma patients.
Chaddad A; Sabri S; Niazi T; Abdulkarim B
Med Biol Eng Comput; 2018 Dec; 56(12):2287-2300. PubMed ID: 29915951
[TBL] [Abstract][Full Text] [Related]
15. Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models.
Kickingereder P; Burth S; Wick A; Götz M; Eidel O; Schlemmer HP; Maier-Hein KH; Wick W; Bendszus M; Radbruch A; Bonekamp D
Radiology; 2016 Sep; 280(3):880-9. PubMed ID: 27326665
[TBL] [Abstract][Full Text] [Related]
16. Combining multimodal imaging and treatment features improves machine learning-based prognostic assessment in patients with glioblastoma multiforme.
Peeken JC; Goldberg T; Pyka T; Bernhofer M; Wiestler B; Kessel KA; Tafti PD; Nüsslin F; Braun AE; Zimmer C; Rost B; Combs SE
Cancer Med; 2019 Jan; 8(1):128-136. PubMed ID: 30561851
[TBL] [Abstract][Full Text] [Related]
17. Machine learning and radiomic phenotyping of lower grade gliomas: improving survival prediction.
Choi YS; Ahn SS; Chang JH; Kang SG; Kim EH; Kim SH; Jain R; Lee SK
Eur Radiol; 2020 Jul; 30(7):3834-3842. PubMed ID: 32162004
[TBL] [Abstract][Full Text] [Related]
18. Radiogenomics to characterize the immune-related prognostic signature associated with biological functions in glioblastoma.
Liu D; Chen J; Ge H; Yan Z; Luo B; Hu X; Yang K; Liu Y; Liu H; Zhang W
Eur Radiol; 2023 Jan; 33(1):209-220. PubMed ID: 35881182
[TBL] [Abstract][Full Text] [Related]
19. Diffusion tensor imaging-based machine learning for IDH wild-type glioblastoma stratification to reveal the biological underpinning of radiomic features.
Wang Z; Guan F; Duan W; Guo Y; Pei D; Qiu Y; Wang M; Xing A; Liu Z; Yu B; Zheng H; Liu X; Yan D; Ji Y; Cheng J; Yan J; Zhang Z
CNS Neurosci Ther; 2023 Nov; 29(11):3339-3350. PubMed ID: 37222229
[TBL] [Abstract][Full Text] [Related]
20. Radiomic MRI Phenotyping of Glioblastoma: Improving Survival Prediction.
Bae S; Choi YS; Ahn SS; Chang JH; Kang SG; Kim EH; Kim SH; Lee SK
Radiology; 2018 Dec; 289(3):797-806. PubMed ID: 30277442
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
