155 related articles for article (PubMed ID: 38568950)
1. Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm.
Wang L; Wang H; D'Angelo F; Curtin L; Sereduk CP; Leon G; Singleton KW; Urcuyo J; Hawkins-Daarud A; Jackson PR; Krishna C; Zimmerman RS; Patra DP; Bendok BR; Smith KA; Nakaji P; Donev K; Baxter LC; Mrugała MM; Ceccarelli M; Iavarone A; Swanson KR; Tran NL; Hu LS; Li J
PLoS One; 2024; 19(4):e0299267. PubMed ID: 38568950
[TBL] [Abstract][Full Text] [Related]
2. Radiogenomics to characterize regional genetic heterogeneity in glioblastoma.
Hu LS; Ning S; Eschbacher JM; Baxter LC; Gaw N; Ranjbar S; Plasencia J; Dueck AC; Peng S; Smith KA; Nakaji P; Karis JP; Quarles CC; Wu T; Loftus JC; Jenkins RB; Sicotte H; Kollmeyer TM; O'Neill BP; Elmquist W; Hoxworth JM; Frakes D; Sarkaria J; Swanson KR; Tran NL; Li J; Mitchell JR
Neuro Oncol; 2017 Jan; 19(1):128-137. PubMed ID: 27502248
[TBL] [Abstract][Full Text] [Related]
3. Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma.
Hu LS; Ning S; Eschbacher JM; Gaw N; Dueck AC; Smith KA; Nakaji P; Plasencia J; Ranjbar S; Price SJ; Tran N; Loftus J; Jenkins R; O'Neill BP; Elmquist W; Baxter LC; Gao F; Frakes D; Karis JP; Zwart C; Swanson KR; Sarkaria J; Wu T; Mitchell JR; Li J
PLoS One; 2015; 10(11):e0141506. PubMed ID: 26599106
[TBL] [Abstract][Full Text] [Related]
4. Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma.
Hu LS; Wang L; Hawkins-Daarud A; Eschbacher JM; Singleton KW; Jackson PR; Clark-Swanson K; Sereduk CP; Peng S; Wang P; Wang J; Baxter LC; Smith KA; Mazza GL; Stokes AM; Bendok BR; Zimmerman RS; Krishna C; Porter AB; Mrugala MM; Hoxworth JM; Wu T; Tran NL; Swanson KR; Li J
Sci Rep; 2021 Feb; 11(1):3932. PubMed ID: 33594116
[TBL] [Abstract][Full Text] [Related]
5. Prediction of IDH1 Mutation Status in Glioblastoma Using Machine Learning Technique Based on Quantitative Radiomic Data.
Lee MH; Kim J; Kim ST; Shin HM; You HJ; Choi JW; Seol HJ; Nam DH; Lee JI; Kong DS
World Neurosurg; 2019 May; 125():e688-e696. PubMed ID: 30735871
[TBL] [Abstract][Full Text] [Related]
6. A generalized parametric response mapping method for analysis of multi-parametric imaging: A feasibility study with application to glioblastoma.
Lausch A; Yeung TP; Chen J; Law E; Wang Y; Urbini B; Donelli F; Manco L; Fainardi E; Lee TY; Wong E
Med Phys; 2017 Nov; 44(11):6074-6084. PubMed ID: 28875538
[TBL] [Abstract][Full Text] [Related]
7. The effect of glioblastoma heterogeneity on survival stratification: a multimodal MR imaging texture analysis.
Liu Y; Zhang X; Feng N; Yin L; He Y; Xu X; Lu H
Acta Radiol; 2018 Oct; 59(10):1239-1246. PubMed ID: 29430935
[TBL] [Abstract][Full Text] [Related]
8. Radiomics for precision medicine in glioblastoma.
Aftab K; Aamir FB; Mallick S; Mubarak F; Pope WB; Mikkelsen T; Rock JP; Enam SA
J Neurooncol; 2022 Jan; 156(2):217-231. PubMed ID: 35020109
[TBL] [Abstract][Full Text] [Related]
9. Integration of machine learning and mechanistic models accurately predicts variation in cell density of glioblastoma using multiparametric MRI.
Gaw N; Hawkins-Daarud A; Hu LS; Yoon H; Wang L; Xu Y; Jackson PR; Singleton KW; Baxter LC; Eschbacher J; Gonzales A; Nespodzany A; Smith K; Nakaji P; Mitchell JR; Wu T; Swanson KR; Li J
Sci Rep; 2019 Jul; 9(1):10063. PubMed ID: 31296889
[TBL] [Abstract][Full Text] [Related]
10. Improving MGMT methylation status prediction of glioblastoma through optimizing radiomics features using genetic algorithm-based machine learning approach.
Do DT; Yang MR; Lam LHT; Le NQK; Wu YW
Sci Rep; 2022 Aug; 12(1):13412. PubMed ID: 35927323
[TBL] [Abstract][Full Text] [Related]
11. Combined unsupervised-supervised classification of multiparametric PET/MRI data: application to prostate cancer.
Gatidis S; Scharpf M; Martirosian P; Bezrukov I; Küstner T; Hennenlotter J; Kruck S; Kaufmann S; Schraml C; la Fougère C; Schwenzer NF; Schmidt H
NMR Biomed; 2015 Jul; 28(7):914-22. PubMed ID: 26014883
[TBL] [Abstract][Full Text] [Related]
12. Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.
Vidić I; Egnell L; Jerome NP; Teruel JR; Sjøbakk TE; Østlie A; Fjøsne HE; Bathen TF; Goa PE
J Magn Reson Imaging; 2018 May; 47(5):1205-1216. PubMed ID: 29044896
[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. In vivo evaluation of EGFRvIII mutation in primary glioblastoma patients via complex multiparametric MRI signature.
Akbari H; Bakas S; Pisapia JM; Nasrallah MP; Rozycki M; Martinez-Lage M; Morrissette JJD; Dahmane N; O'Rourke DM; Davatzikos C
Neuro Oncol; 2018 Jul; 20(8):1068-1079. PubMed ID: 29617843
[TBL] [Abstract][Full Text] [Related]
15. Investigating the Role of Image Fusion in Brain Tumor Classification Models Based on Machine Learning Algorithm for Personalized Medicine.
Nanmaran R; Srimathi S; Yamuna G; Thanigaivel S; Vickram AS; Priya AK; Karthick A; Karpagam J; Mohanavel V; Muhibbullah M
Comput Math Methods Med; 2022; 2022():7137524. PubMed ID: 35178119
[TBL] [Abstract][Full Text] [Related]
16. Machine-learning based radiogenomics analysis of MRI features and metagenes in glioblastoma multiforme patients with different survival time.
Liao X; Cai B; Tian B; Luo Y; Song W; Li Y
J Cell Mol Med; 2019 Jun; 23(6):4375-4385. PubMed ID: 31001929
[TBL] [Abstract][Full Text] [Related]
17. AI Deployment on GBM Diagnosis: A Novel Approach to Analyze Histopathological Images Using Image Feature-Based Analysis.
Cheung EYW; Wu RWK; Li ASM; Chu ESM
Cancers (Basel); 2023 Oct; 15(20):. PubMed ID: 37894430
[TBL] [Abstract][Full Text] [Related]
18. Radiogenomics of Glioblastoma: Machine Learning-based Classification of Molecular Characteristics by Using Multiparametric and Multiregional MR Imaging Features.
Kickingereder P; Bonekamp D; Nowosielski M; Kratz A; Sill M; Burth S; Wick A; Eidel O; Schlemmer HP; Radbruch A; Debus J; Herold-Mende C; Unterberg A; Jones D; Pfister S; Wick W; von Deimling A; Bendszus M; Capper D
Radiology; 2016 Dec; 281(3):907-918. PubMed ID: 27636026
[TBL] [Abstract][Full Text] [Related]
19. DC-AL GAN: Pseudoprogression and true tumor progression of glioblastoma multiform image classification based on DCGAN and AlexNet.
Li M; Tang H; Chan MD; Zhou X; Qian X
Med Phys; 2020 Mar; 47(3):1139-1150. PubMed ID: 31885094
[TBL] [Abstract][Full Text] [Related]
20. Characterization of breast tumors using machine learning based upon multiparametric magnetic resonance imaging features.
Thakran S; Gupta RK; Singh A
NMR Biomed; 2022 May; 35(5):e4665. PubMed ID: 34962326
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
