BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

175 related articles for article (PubMed ID: 29599461)

  • 1. Using human brain activity to guide machine learning.
    Fong RC; Scheirer WJ; Cox DD
    Sci Rep; 2018 Mar; 8(1):5397. PubMed ID: 29599461
    [TBL] [Abstract][Full Text] [Related]  

  • 2. MRI Gibbs-ringing artifact reduction by means of machine learning using convolutional neural networks.
    Zhang Q; Ruan G; Yang W; Liu Y; Zhao K; Feng Q; Chen W; Wu EX; Feng Y
    Magn Reson Med; 2019 Dec; 82(6):2133-2145. PubMed ID: 31373061
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Semantic segmentation of cerebrospinal fluid and brain volume with a convolutional neural network in pediatric hydrocephalus-transfer learning from existing algorithms.
    Grimm F; Edl F; Kerscher SR; Nieselt K; Gugel I; Schuhmann MU
    Acta Neurochir (Wien); 2020 Oct; 162(10):2463-2474. PubMed ID: 32583085
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Machine learning for evolutive lymphoma and residual masses recognition in whole body diffusion weighted magnetic resonance images.
    Ferjaoui R; Cherni MA; Boujnah S; Kraiem NEH; Kraiem T
    Comput Methods Programs Biomed; 2021 Sep; 209():106320. PubMed ID: 34390938
    [TBL] [Abstract][Full Text] [Related]  

  • 5. BrainNET: Inference of Brain Network Topology Using Machine Learning.
    Murugesan GK; Ganesh C; Nalawade S; Davenport EM; Wagner B; Kim WH; Maldjian JA
    Brain Connect; 2020 Oct; 10(8):422-435. PubMed ID: 33030350
    [No Abstract]   [Full Text] [Related]  

  • 6. Learning-based 3T brain MRI segmentation with guidance from 7T MRI labeling.
    Deng M; Yu R; Wang L; Shi F; Yap PT; Shen D;
    Med Phys; 2016 Dec; 43(12):6588-6597. PubMed ID: 28054724
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Transfer learning of deep neural network representations for fMRI decoding.
    Svanera M; Savardi M; Benini S; Signoroni A; Raz G; Hendler T; Muckli L; Goebel R; Valente G
    J Neurosci Methods; 2019 Dec; 328():108319. PubMed ID: 31585315
    [TBL] [Abstract][Full Text] [Related]  

  • 8. MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques.
    Saeedi S; Rezayi S; Keshavarz H; R Niakan Kalhori S
    BMC Med Inform Decis Mak; 2023 Jan; 23(1):16. PubMed ID: 36691030
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Hybrid Approach Based on Deep CNN and Machine Learning Classifiers for the Tumor Segmentation and Classification in Brain MRI.
    Haq EU; Jianjun H; Huarong X; Li K; Weng L
    Comput Math Methods Med; 2022; 2022():6446680. PubMed ID: 36035291
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine learning and image analysis in vascular surgery.
    Tomihama RT; Dass S; Chen S; Kiang SC
    Semin Vasc Surg; 2023 Sep; 36(3):413-418. PubMed ID: 37863613
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Segmentation of white matter hyperintensities using convolutional neural networks with global spatial information in routine clinical brain MRI with none or mild vascular pathology.
    Rachmadi MF; Valdés-Hernández MDC; Agan MLF; Di Perri C; Komura T;
    Comput Med Imaging Graph; 2018 Jun; 66():28-43. PubMed ID: 29523002
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Segmenting brain tumors from FLAIR MRI using fully convolutional neural networks.
    Ribalta Lorenzo P; Nalepa J; Bobek-Billewicz B; Wawrzyniak P; Mrukwa G; Kawulok M; Ulrych P; Hayball MP
    Comput Methods Programs Biomed; 2019 Jul; 176():135-148. PubMed ID: 31200901
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks.
    Dürr O; Sick B
    J Biomol Screen; 2016 Oct; 21(9):998-1003. PubMed ID: 26950929
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Molecular imaging with neural training of identification algorithm (neural network localization identification).
    Nelson AJ; Hess ST
    Microsc Res Tech; 2018 Sep; 81(9):966-972. PubMed ID: 30242941
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Pharmacologically informed machine learning approach for identifying pathological states of unconsciousness via resting-state fMRI.
    Campbell JM; Huang Z; Zhang J; Wu X; Qin P; Northoff G; Mashour GA; Hudetz AG
    Neuroimage; 2020 Feb; 206():116316. PubMed ID: 31672663
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Automatic brain MRI motion artifact detection based on end-to-end deep learning is similarly effective as traditional machine learning trained on image quality metrics.
    Vakli P; Weiss B; Szalma J; Barsi P; Gyuricza I; Kemenczky P; Somogyi E; Nárai Á; Gál V; Hermann P; Vidnyánszky Z
    Med Image Anal; 2023 Aug; 88():102850. PubMed ID: 37263108
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Group-representative functional network estimation from multi-subject fMRI data via MRF-based image segmentation.
    Tang B; Iyer A; Rao V; Kong N
    Comput Methods Programs Biomed; 2019 Oct; 179():104976. PubMed ID: 31443856
    [TBL] [Abstract][Full Text] [Related]  

  • 18. MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers.
    Kang J; Ullah Z; Gwak J
    Sensors (Basel); 2021 Mar; 21(6):. PubMed ID: 33810176
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A Novel Deep Learning Algorithm for the Automatic Detection of High-Grade Gliomas on T2-Weighted Magnetic Resonance Images: A Preliminary Machine Learning Study.
    Atici MA; Sagiroglu S; Celtikci P; Ucar M; Borcek AO; Emmez H; Celtikci E
    Turk Neurosurg; 2020; 30(2):199-205. PubMed ID: 31608975
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach.
    Romeo V; Maurea S; Cuocolo R; Petretta M; Mainenti PP; Verde F; Coppola M; Dell'Aversana S; Brunetti A
    J Magn Reson Imaging; 2018 Jul; 48(1):198-204. PubMed ID: 29341325
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.