These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

657 related articles for article (PubMed ID: 36246951)

  • 1. Deepfakes in Ophthalmology: Applications and Realism of Synthetic Retinal Images from Generative Adversarial Networks.
    Chen JS; Coyner AS; Chan RVP; Hartnett ME; Moshfeghi DM; Owen LA; Kalpathy-Cramer J; Chiang MF; Campbell JP
    Ophthalmol Sci; 2021 Dec; 1(4):100079. PubMed ID: 36246951
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. 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]  

  • 4. SynthEye: Investigating the Impact of Synthetic Data on Artificial Intelligence-assisted Gene Diagnosis of Inherited Retinal Disease.
    Veturi YA; Woof W; Lazebnik T; Moghul I; Woodward-Court P; Wagner SK; Cabral de Guimarães TA; Daich Varela M; Liefers B; Patel PJ; Beck S; Webster AR; Mahroo O; Keane PA; Michaelides M; Balaskas K; Pontikos N
    Ophthalmol Sci; 2023 Jun; 3(2):100258. PubMed ID: 36685715
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Synthetic artificial intelligence using generative adversarial network for retinal imaging in detection of age-related macular degeneration.
    Wang Z; Lim G; Ng WY; Tan TE; Lim J; Lim SH; Foo V; Lim J; Sinisterra LG; Zheng F; Liu N; Tan GSW; Cheng CY; Cheung GCM; Wong TY; Ting DSW
    Front Med (Lausanne); 2023; 10():1184892. PubMed ID: 37425325
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Assessment of Generative Adversarial Networks Model for Synthetic Optical Coherence Tomography Images of Retinal Disorders.
    Zheng C; Xie X; Zhou K; Chen B; Chen J; Ye H; Li W; Qiao T; Gao S; Yang J; Liu J
    Transl Vis Sci Technol; 2020 May; 9(2):29. PubMed ID: 32832202
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. ROP-GAN: an image synthesis method for retinopathy of prematurity based on generative adversarial network.
    Hou N; Shi J; Ding X; Nie C; Wang C; Wan J
    Phys Med Biol; 2023 Oct; 68(20):. PubMed ID: 37619572
    [No Abstract]   [Full Text] [Related]  

  • 9. Evaluation of Generative Adversarial Networks for High-Resolution Synthetic Image Generation of Circumpapillary Optical Coherence Tomography Images for Glaucoma.
    Sreejith Kumar AJ; Chong RS; Crowston JG; Chua J; Bujor I; Husain R; Vithana EN; Girard MJA; Ting DSW; Cheng CY; Aung T; Popa-Cherecheanu A; Schmetterer L; Wong D
    JAMA Ophthalmol; 2022 Oct; 140(10):974-981. PubMed ID: 36048435
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. 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]  

  • 12. Retinal image synthesis from multiple-landmarks input with generative adversarial networks.
    Yu Z; Xiang Q; Meng J; Kou C; Ren Q; Lu Y
    Biomed Eng Online; 2019 May; 18(1):62. PubMed ID: 31113438
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Generative artificial intelligence in ophthalmology.
    Waisberg E; Ong J; Kamran SA; Masalkhi M; Paladugu P; Zaman N; Lee AG; Tavakkoli A
    Surv Ophthalmol; 2025; 70(1):1-11. PubMed ID: 38762072
    [TBL] [Abstract][Full Text] [Related]  

  • 14. RF-GANs: A Method to Synthesize Retinal Fundus Images Based on Generative Adversarial Network.
    Chen Y; Long J; Guo J
    Comput Intell Neurosci; 2021; 2021():3812865. PubMed ID: 34804140
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Using a Visual Turing Test to Evaluate the Realism of Generative Adversarial Network (GAN)-Based Synthesized Myocardial Perfusion Images.
    Higaki A; Kawada Y; Hiasa G; Yamada T; Okayama H
    Cureus; 2022 Oct; 14(10):e30646. PubMed ID: 36439582
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Diagnosability of Synthetic Retinal Fundus Images for Plus Disease Detection in Retinopathy of Prematurity.
    Coyner AS; Chen J; Campbell JP; Ostmo S; Singh P; Kalpathy-Cramer J; Chiang MF
    AMIA Annu Symp Proc; 2020; 2020():329-337. PubMed ID: 33936405
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Perceived Realism of High-Resolution Generative Adversarial Network-derived Synthetic Mammograms.
    Korkinof D; Harvey H; Heindl A; Karpati E; Williams G; Rijken T; Kecskemethy P; Glocker B
    Radiol Artif Intell; 2021 Mar; 3(2):e190181. PubMed ID: 33937856
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Improving synthetic media generation and detection using generative adversarial networks.
    Zia R; Rehman M; Hussain A; Nazeer S; Anjum M
    PeerJ Comput Sci; 2024; 10():e2181. PubMed ID: 39314737
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Generative Adversarial Networks Can Create High Quality Artificial Prostate Cancer Magnetic Resonance Images.
    Xu IRL; Van Booven DJ; Goberdhan S; Breto A; Porto J; Alhusseini M; Algohary A; Stoyanova R; Punnen S; Mahne A; Arora H
    J Pers Med; 2023 Mar; 13(3):. PubMed ID: 36983728
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Generating Synthesized Fluorescein Angiography Images From Color Fundus Images by Generative Adversarial Networks for Macular Edema Assessment.
    Xie X; Jiachu D; Liu C; Xie M; Guo J; Cai K; Li X; Mi W; Ye H; Luo L; Yang J; Zhang M; Zheng C
    Transl Vis Sci Technol; 2024 Sep; 13(9):26. PubMed ID: 39312216
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 33.