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Journal Abstract Search

224 related items for PubMed ID: 36086040

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  • 4. Transfer learning-driven ensemble model for detection of diabetic retinopathy disease.
    Chaurasia BK, Raj H, Rathour SS, Singh PB.
    Med Biol Eng Comput; 2023 Aug; 61(8):2033-2049. PubMed ID: 37296285
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  • 5. Artificial intelligence based glaucoma and diabetic retinopathy detection using MATLAB - retrained AlexNet convolutional neural network.
    Arias-Serrano I, Velásquez-López PA, Avila-Briones LN, Laurido-Mora FC, Villalba-Meneses F, Tirado-Espin A, Cruz-Varela J, Almeida-Galárraga D.
    F1000Res; 2023 Aug; 12():14. PubMed ID: 38826575
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  • 6. Performance Analysis of Deep-Neural-Network-Based Automatic Diagnosis of Diabetic Retinopathy.
    Tariq H, Rashid M, Javed A, Zafar E, Alotaibi SS, Zia MYI.
    Sensors (Basel); 2021 Dec 29; 22(1):. PubMed ID: 35009747
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  • 7. A deep learning framework for the early detection of multi-retinal diseases.
    Ejaz S, Baig R, Ashraf Z, Alnfiai MM, Alnahari MM, Alotaibi RM.
    PLoS One; 2024 Dec 29; 19(7):e0307317. PubMed ID: 39052616
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  • 8. Automated detection of diabetic retinopathy using custom convolutional neural network.
    Albahli S, Ahmad Hassan Yar GN.
    J Xray Sci Technol; 2022 Dec 29; 30(2):275-291. PubMed ID: 35001904
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  • 9. Diabetic Retinopathy Fundus Image Classification and Lesions Localization System Using Deep Learning.
    Alyoubi WL, Abulkhair MF, Shalash WM.
    Sensors (Basel); 2021 May 26; 21(11):. PubMed ID: 34073541
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  • 13. End-to-end diabetic retinopathy grading based on fundus fluorescein angiography images using deep learning.
    Gao Z, Jin K, Yan Y, Liu X, Shi Y, Ge Y, Pan X, Lu Y, Wu J, Wang Y, Ye J.
    Graefes Arch Clin Exp Ophthalmol; 2022 May 26; 260(5):1663-1673. PubMed ID: 35066704
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  • 15. Ensemble of deep convolutional neural networks is more accurate and reliable than board-certified ophthalmologists at detecting multiple diseases in retinal fundus photographs.
    Pandey PU, Ballios BG, Christakis PG, Kaplan AJ, Mathew DJ, Ong Tone S, Wan MJ, Micieli JA, Wong JCY.
    Br J Ophthalmol; 2024 Feb 21; 108(3):417-423. PubMed ID: 36720585
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  • 16. A computer-aided diagnosis system for detecting various diabetic retinopathy grades based on a hybrid deep learning technique.
    AbdelMaksoud E, Barakat S, Elmogy M.
    Med Biol Eng Comput; 2022 Jul 21; 60(7):2015-2038. PubMed ID: 35545738
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  • 17. Referable diabetic retinopathy identification from eye fundus images with weighted path for convolutional neural network.
    Liu YP, Li Z, Xu C, Li J, Liang R.
    Artif Intell Med; 2019 Aug 21; 99():101694. PubMed ID: 31606108
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  • 18. 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, Imaging and Informatics in Retinopathy of Prematurity Consortium.
    Ophthalmol Sci; 2022 Jun 21; 2(2):100126. PubMed ID: 36249693
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  • 19. Transfer Learning for Automated OCTA Detection of Diabetic Retinopathy.
    Le D, Alam M, Yao CK, Lim JI, Hsieh YT, Chan RVP, Toslak D, Yao X.
    Transl Vis Sci Technol; 2020 Jul 21; 9(2):35. PubMed ID: 32855839
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  • 20. Diabetic retinopathy detection through convolutional neural networks with synaptic metaplasticity.
    Vives-Boix V, Ruiz-Fernández D.
    Comput Methods Programs Biomed; 2021 Jul 21; 206():106094. PubMed ID: 34010801
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