BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

260 related articles for article (PubMed ID: 32694637)

  • 21. Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques.
    Suter Y; Knecht U; Alão M; Valenzuela W; Hewer E; Schucht P; Wiest R; Reyes M
    Cancer Imaging; 2020 Aug; 20(1):55. PubMed ID: 32758279
    [TBL] [Abstract][Full Text] [Related]  

  • 22. A Coclinical Radiogenomic Validation Study: Conserved Magnetic Resonance Radiomic Appearance of Periostin-Expressing Glioblastoma in Patients and Xenograft Models.
    Zinn PO; Singh SK; Kotrotsou A; Hassan I; Thomas G; Luedi MM; Elakkad A; Elshafeey N; Idris T; Mosley J; Gumin J; Fuller GN; de Groot JF; Baladandayuthapani V; Sulman EP; Kumar AJ; Sawaya R; Lang FF; Piwnica-Worms D; Colen RR
    Clin Cancer Res; 2018 Dec; 24(24):6288-6299. PubMed ID: 30054278
    [TBL] [Abstract][Full Text] [Related]  

  • 23. MRI Radiomic Features to Predict IDH1 Mutation Status in Gliomas: A Machine Learning Approach using Gradient Tree Boosting.
    Sakai Y; Yang C; Kihira S; Tsankova N; Khan F; Hormigo A; Lai A; Cloughesy T; Nael K
    Int J Mol Sci; 2020 Oct; 21(21):. PubMed ID: 33121211
    [TBL] [Abstract][Full Text] [Related]  

  • 24. 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]  

  • 25. AI-based classification of three common malignant tumors in neuro-oncology: A multi-institutional comparison of machine learning and deep learning methods.
    Bathla G; Dhruba DD; Soni N; Liu Y; Larson NB; Kassmeyer BA; Mohan S; Roberts-Wolfe D; Rathore S; Le NH; Zhang H; Sonka M; Priya S
    J Neuroradiol; 2024 May; 51(3):258-264. PubMed ID: 37652263
    [TBL] [Abstract][Full Text] [Related]  

  • 26. The Nomogram of MRI-based Radiomics with Complementary Visual Features by Machine Learning Improves Stratification of Glioblastoma Patients: A Multicenter Study.
    Xu Y; He X; Li Y; Pang P; Shu Z; Gong X
    J Magn Reson Imaging; 2021 Aug; 54(2):571-583. PubMed ID: 33559302
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Prediction of Response to Stereotactic Radiosurgery for Brain Metastases Using Convolutional Neural Networks.
    Cha YJ; Jang WI; Kim MS; Yoo HJ; Paik EK; Jeong HK; Youn SM
    Anticancer Res; 2018 Sep; 38(9):5437-5445. PubMed ID: 30194200
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Differentiation Between Glioblastoma Multiforme and Metastasis From the Lungs and Other Sites Using Combined Clinical/Routine MRI Radiomics.
    Han Y; Zhang L; Niu S; Chen S; Yang B; Chen H; Zheng F; Zang Y; Zhang H; Xin Y; Chen X
    Front Cell Dev Biol; 2021; 9():710461. PubMed ID: 34513840
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Development of a Machine Learning Classifier Based on Radiomic Features Extracted From Post-Contrast 3D T1-Weighted MR Images to Distinguish Glioblastoma From Solitary Brain Metastasis.
    de Causans A; Carré A; Roux A; Tauziède-Espariat A; Ammari S; Dezamis E; Dhermain F; Reuzé S; Deutsch E; Oppenheim C; Varlet P; Pallud J; Edjlali M; Robert C
    Front Oncol; 2021; 11():638262. PubMed ID: 34327133
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Development and Validation of a Deep Learning Radiomics Model Predicting Lymph Node Status in Operable Cervical Cancer.
    Dong T; Yang C; Cui B; Zhang T; Sun X; Song K; Wang L; Kong B; Yang X
    Front Oncol; 2020; 10():464. PubMed ID: 32373511
    [No Abstract]   [Full Text] [Related]  

  • 31. Distinguishing True Progression From Radionecrosis After Stereotactic Radiation Therapy for Brain Metastases With Machine Learning and Radiomics.
    Peng L; Parekh V; Huang P; Lin DD; Sheikh K; Baker B; Kirschbaum T; Silvestri F; Son J; Robinson A; Huang E; Ames H; Grimm J; Chen L; Shen C; Soike M; McTyre E; Redmond K; Lim M; Lee J; Jacobs MA; Kleinberg L
    Int J Radiat Oncol Biol Phys; 2018 Nov; 102(4):1236-1243. PubMed ID: 30353872
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Discrimination Between Glioblastoma and Solitary Brain Metastasis Using Conventional MRI and Diffusion-Weighted Imaging Based on a Deep Learning Algorithm.
    Yan Q; Li F; Cui Y; Wang Y; Wang X; Jia W; Liu X; Li Y; Chang H; Shi F; Xia Y; Zhou Q; Zeng Q
    J Digit Imaging; 2023 Aug; 36(4):1480-1488. PubMed ID: 37156977
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Distinct tumor signatures using deep learning-based characterization of the peritumoral microenvironment in glioblastomas and brain metastases.
    Samani ZR; Parker D; Wolf R; Hodges W; Brem S; Verma R
    Sci Rep; 2021 Jul; 11(1):14469. PubMed ID: 34262079
    [TBL] [Abstract][Full Text] [Related]  

  • 34. 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]  

  • 35. Development and Validation of a MRI-Based Radiomics Prognostic Classifier in Patients with Primary Glioblastoma Multiforme.
    Chen X; Fang M; Dong D; Liu L; Xu X; Wei X; Jiang X; Qin L; Liu Z
    Acad Radiol; 2019 Oct; 26(10):1292-1300. PubMed ID: 30660472
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Radiomics in peritumoral non-enhancing regions: fractional anisotropy and cerebral blood volume improve prediction of local progression and overall survival in patients with glioblastoma.
    Kim JY; Yoon MJ; Park JE; Choi EJ; Lee J; Kim HS
    Neuroradiology; 2019 Nov; 61(11):1261-1272. PubMed ID: 31289886
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Multiregional radiomics profiling from multiparametric MRI: Identifying an imaging predictor of IDH1 mutation status in glioblastoma.
    Li ZC; Bai H; Sun Q; Zhao Y; Lv Y; Zhou J; Liang C; Chen Y; Liang D; Zheng H
    Cancer Med; 2018 Dec; 7(12):5999-6009. PubMed ID: 30426720
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Clinical Value of Vascular Permeability Estimates Using Dynamic Susceptibility Contrast MRI: Improved Diagnostic Performance in Distinguishing Hypervascular Primary CNS Lymphoma from Glioblastoma.
    Lee B; Park JE; Bjørnerud A; Kim JH; Lee JY; Kim HS
    AJNR Am J Neuroradiol; 2018 Aug; 39(8):1415-1422. PubMed ID: 30026384
    [TBL] [Abstract][Full Text] [Related]  

  • 39. 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]  

  • 40. 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]  

    [Previous]   [Next]    [New Search]
    of 13.