128 related articles for article (PubMed ID: 37507329)
1. Development and External Validation of an MRI-based Radiomics Nomogram to Distinguish Circumscribed Astrocytic Gliomas and Diffuse Gliomas: A Multicenter Study.
Li S; Su X; Peng J; Chen N; Liu Y; Zhang S; Shao H; Tan Q; Yang X; Liu Y; Gong Q; Yue Q
Acad Radiol; 2024 Feb; 31(2):639-647. PubMed ID: 37507329
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. A fully automatic multiparametric radiomics model for differentiation of adult pilocytic astrocytomas from high-grade gliomas.
Park YW; Eom J; Kim D; Ahn SS; Kim EH; Kang SG; Chang JH; Kim SH; Lee SK
Eur Radiol; 2022 Jul; 32(7):4500-4509. PubMed ID: 35141780
[TBL] [Abstract][Full Text] [Related]
4. Machine learning-based multiparametric magnetic resonance imaging radiomics model for distinguishing central neurocytoma from glioma of lateral ventricle.
Mo H; Liang W; Huang Z; Li X; Xiao X; Liu H; He J; Xu Y; Wu Y
Eur Radiol; 2023 Jun; 33(6):4259-4269. PubMed ID: 36547672
[TBL] [Abstract][Full Text] [Related]
5. A radiomics nomogram may improve the prediction of IDH genotype for astrocytoma before surgery.
Tan Y; Zhang ST; Wei JW; Dong D; Wang XC; Yang GQ; Tian J; Zhang H
Eur Radiol; 2019 Jul; 29(7):3325-3337. PubMed ID: 30972543
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Radiomics Nomogram Building From Multiparametric MRI to Predict Grade in Patients With Glioma: A Cohort Study.
Wang Q; Li Q; Mi R; Ye H; Zhang H; Chen B; Li Y; Huang G; Xia J
J Magn Reson Imaging; 2019 Mar; 49(3):825-833. PubMed ID: 30260592
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Genotype prediction of ATRX mutation in lower-grade gliomas using an MRI radiomics signature.
Li Y; Liu X; Qian Z; Sun Z; Xu K; Wang K; Fan X; Zhang Z; Li S; Wang Y; Jiang T
Eur Radiol; 2018 Jul; 28(7):2960-2968. PubMed ID: 29404769
[TBL] [Abstract][Full Text] [Related]
10. Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma.
Chen YD; Zhang L; Zhou ZP; Lin B; Jiang ZJ; Tang C; Dang YW; Xia YW; Song B; Long LL
World J Gastroenterol; 2022 Aug; 28(31):4399-4416. PubMed ID: 36159011
[TBL] [Abstract][Full Text] [Related]
11. Diffusion-weighted imaging and arterial spin labeling radiomics features may improve differentiation between radiation-induced brain injury and glioma recurrence.
Zhang J; Wu Y; Wang Y; Zhang X; Lei Y; Zhu G; Mao C; Zhang L; Ma L
Eur Radiol; 2023 May; 33(5):3332-3342. PubMed ID: 36576544
[TBL] [Abstract][Full Text] [Related]
12. Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study.
Yu Y; He Z; Ouyang J; Tan Y; Chen Y; Gu Y; Mao L; Ren W; Wang J; Lin L; Wu Z; Liu J; Ou Q; Hu Q; Li A; Chen K; Li C; Lu N; Li X; Su F; Liu Q; Xie C; Yao H
EBioMedicine; 2021 Jul; 69():103460. PubMed ID: 34233259
[TBL] [Abstract][Full Text] [Related]
13. Multimodal MRI-based radiomic nomogram for predicting telomerase reverse transcriptase promoter mutation in IDH-wildtype histological lower-grade gliomas.
Huo X; Wang Y; Ma S; Zhu S; Wang K; Ji Q; Chen F; Wang L; Wu Z; Li W
Medicine (Baltimore); 2023 Dec; 102(51):e36581. PubMed ID: 38134061
[TBL] [Abstract][Full Text] [Related]
14. Leveraging multimodal MRI-based radiomics analysis with diverse machine learning models to evaluate lymphovascular invasion in clinically node-negative breast cancer.
Jiang Y; Zeng Y; Zuo Z; Yang X; Liu H; Zhou Y; Fan X
Heliyon; 2024 Jan; 10(1):e23916. PubMed ID: 38192872
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Amide proton transfer-weighted imaging and derived radiomics in the classification of adult-type diffuse gliomas.
Wu M; Jiang T; Guo M; Duan Y; Zhuo Z; Weng J; Xie C; Sun J; Li J; Cheng D; Liu X; Du J; Zhang X; Zhang Y; Liu Y
Eur Radiol; 2023 Oct; ():. PubMed ID: 37855851
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas.
Park CJ; Han K; Kim H; Ahn SS; Choi YS; Park YW; Chang JH; Kim SH; Jain R; Lee SK
Eur Radiol; 2020 Dec; 30(12):6464-6474. PubMed ID: 32740813
[TBL] [Abstract][Full Text] [Related]
19. Non-invasive genotype prediction of chromosome 1p/19q co-deletion by development and validation of an MRI-based radiomics signature in lower-grade gliomas.
Han Y; Xie Z; Zang Y; Zhang S; Gu D; Zhou M; Gevaert O; Wei J; Li C; Chen H; Du J; Liu Z; Dong D; Tian J; Zhou D
J Neurooncol; 2018 Nov; 140(2):297-306. PubMed ID: 30097822
[TBL] [Abstract][Full Text] [Related]
20. Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics for Prediction of H3K27M Mutation in Midline Gliomas.
Kandemirli SG; Kocak B; Naganawa S; Ozturk K; Yip SSF; Chopra S; Rivetti L; Aldine AS; Jones K; Cayci Z; Moritani T; Sato TS
World Neurosurg; 2021 Jul; 151():e78-e85. PubMed ID: 33819703
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
