BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

270 related articles for article (PubMed ID: 36015906)

  • 1. Deep Convolutional Generative Adversarial Networks to Enhance Artificial Intelligence in Healthcare: A Skin Cancer Application.
    La Salvia M; Torti E; Leon R; Fabelo H; Ortega S; Martinez-Vega B; Callico GM; Leporati F
    Sensors (Basel); 2022 Aug; 22(16):. PubMed ID: 36015906
    [TBL] [Abstract][Full Text] [Related]  

  • 2. An IoMT-Based Melanoma Lesion Segmentation Using Conditional Generative Adversarial Networks.
    Ali Z; Naz S; Zaffar H; Choi J; Kim Y
    Sensors (Basel); 2023 Mar; 23(7):. PubMed ID: 37050607
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Synthetic Medical Images for Robust, Privacy-Preserving Training of Artificial Intelligence: Application to Retinopathy of Prematurity Diagnosis.
    Coyner AS; Chen JS; Chang K; Singh P; Ostmo S; Chan RVP; Chiang MF; Kalpathy-Cramer J; Campbell JP;
    Ophthalmol Sci; 2022 Jun; 2(2):100126. PubMed ID: 36249693
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Brain Tumor Classification Using a Combination of Variational Autoencoders and Generative Adversarial Networks.
    Ahmad B; Sun J; You Q; Palade V; Mao Z
    Biomedicines; 2022 Jan; 10(2):. PubMed ID: 35203433
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Automatic generation of artificial images of leukocytes and leukemic cells using generative adversarial networks (syntheticcellgan).
    Barrera K; Merino A; Molina A; Rodellar J
    Comput Methods Programs Biomed; 2023 Feb; 229():107314. PubMed ID: 36565666
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Understanding Deep Convolutional Networks for Biomedical Imaging: A Practical Tutorial.
    Huang D; Feng M
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():857-863. PubMed ID: 31946030
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Artificial Intelligence in Diagnostic Radiology: Where Do We Stand, Challenges, and Opportunities.
    Moawad AW; Fuentes DT; ElBanan MG; Shalaby AS; Guccione J; Kamel S; Jensen CT; Elsayes KM
    J Comput Assist Tomogr; 2022 Jan-Feb 01; 46(1):78-90. PubMed ID: 35027520
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Progressive growing of Generative Adversarial Networks for improving data augmentation and skin cancer diagnosis.
    Pérez E; Ventura S
    Artif Intell Med; 2023 Jul; 141():102556. PubMed ID: 37295899
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Generating ultrasonic images indistinguishable from real images using Generative Adversarial Networks.
    Posilović L; Medak D; Subašić M; Budimir M; Lončarić S
    Ultrasonics; 2022 Feb; 119():106610. PubMed ID: 34735930
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Creating High Fidelity Synthetic Pelvis Radiographs Using Generative Adversarial Networks: Unlocking the Potential of Deep Learning Models Without Patient Privacy Concerns.
    Khosravi B; Rouzrokh P; Mickley JP; Faghani S; Larson AN; Garner HW; Howe BM; Erickson BJ; Taunton MJ; Wyles CC
    J Arthroplasty; 2023 Oct; 38(10):2037-2043.e1. PubMed ID: 36535448
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Combating COVID-19 Using Generative Adversarial Networks and Artificial Intelligence for Medical Images: Scoping Review.
    Ali H; Shah Z
    JMIR Med Inform; 2022 Jun; 10(6):e37365. PubMed ID: 35709336
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Discrimination of unsound wheat kernels based on deep convolutional generative adversarial network and near-infrared hyperspectral imaging technology.
    Li H; Zhang L; Sun H; Rao Z; Ji H
    Spectrochim Acta A Mol Biomol Spectrosc; 2022 Mar; 268():120722. PubMed ID: 34902690
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Generative Adversarial Networks: A Primer for Radiologists.
    Wolterink JM; Mukhopadhyay A; Leiner T; Vogl TJ; Bucher AM; Išgum I
    Radiographics; 2021; 41(3):840-857. PubMed ID: 33891522
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Generating Hyperspectral Skin Cancer Imagery using Generative Adversarial Neural Network.
    Annala L; Neittaanmaki N; Paoli J; Zaar O; Polonen I
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1600-1603. PubMed ID: 33018300
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Assessment of Deep Generative Models for High-Resolution Synthetic Retinal Image Generation of Age-Related Macular Degeneration.
    Burlina PM; Joshi N; Pacheco KD; Liu TYA; Bressler NM
    JAMA Ophthalmol; 2019 Mar; 137(3):258-264. PubMed ID: 30629091
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Generative adversarial networks in ophthalmology: what are these and how can they be used?
    Wang Z; Lim G; Ng WY; Keane PA; Campbell JP; Tan GSW; Schmetterer L; Wong TY; Liu Y; Ting DSW
    Curr Opin Ophthalmol; 2021 Sep; 32(5):459-467. PubMed ID: 34324454
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A generative adversarial inpainting network to enhance prediction of periodontal clinical attachment level.
    Kearney VP; Yansane AM; Brandon RG; Vaderhobli R; Lin GH; Hekmatian H; Deng W; Joshi N; Bhandari H; Sadat AS; White JM
    J Dent; 2022 Aug; 123():104211. PubMed ID: 35760207
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Medical image analysis using deep learning algorithms.
    Li M; Jiang Y; Zhang Y; Zhu H
    Front Public Health; 2023; 11():1273253. PubMed ID: 38026291
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Generative artificial intelligence: synthetic datasets in dentistry.
    Umer F; Adnan N
    BDJ Open; 2024 Mar; 10(1):13. PubMed ID: 38429258
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Can Synthetic Images Improve CNN Performance in Wound Image Classification?
    Malihi L; Hübner U; Richter ML; Moelleken M; Przysucha M; Busch D; Heggemann J; Hafer G; Wiemeyer S; Heidemann G; Dissemond J; Erfurt-Berge C; Barkhau C; Hendriks A; Hüsers J
    Stud Health Technol Inform; 2023 May; 302():927-931. PubMed ID: 37203538
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.