BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

192 related articles for article (PubMed ID: 35342328)

  • 1. A critical review on diagnosis of diabetic retinopathy using machine learning and deep learning.
    Das D; Biswas SK; Bandyopadhyay S
    Multimed Tools Appl; 2022; 81(18):25613-25655. PubMed ID: 35342328
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Combining transfer learning with retinal lesion features for accurate detection of diabetic retinopathy.
    Hassan D; Gill HM; Happe M; Bhatwadekar AD; Hajrasouliha AR; Janga SC
    Front Med (Lausanne); 2022; 9():1050436. PubMed ID: 36425113
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Detection of Diabetic Retinopathy using Convolutional Neural Networks for Feature Extraction and Classification (DRFEC).
    Das D; Biswas SK; Bandyopadhyay S
    Multimed Tools Appl; 2022 Nov; ():1-59. PubMed ID: 36467440
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Review on diabetic retinopathy with deep learning methods.
    Shekar S; Satpute N; Gupta A
    J Med Imaging (Bellingham); 2021 Nov; 8(6):060901. PubMed ID: 34859116
    [No Abstract]   [Full Text] [Related]  

  • 5. Deep learning innovations in diagnosing diabetic retinopathy: The potential of transfer learning and the DiaCNN model.
    Shoaib MR; Emara HM; Zhao J; El-Shafai W; Soliman NF; Mubarak AS; Omer OA; El-Samie FEA; Esmaiel H
    Comput Biol Med; 2024 Feb; 169():107834. PubMed ID: 38159396
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Machine Learning Ensemble Classifier for Early Prediction of Diabetic Retinopathy.
    S K S; P A
    J Med Syst; 2017 Nov; 41(12):201. PubMed ID: 29124453
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep learning based computer-aided diagnosis systems for diabetic retinopathy: A survey.
    Asiri N; Hussain M; Al Adel F; Alzaidi N
    Artif Intell Med; 2019 Aug; 99():101701. PubMed ID: 31606116
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Diabetic Retinopathy Fundus Image Classification and Lesions Localization System Using Deep Learning.
    Alyoubi WL; Abulkhair MF; Shalash WM
    Sensors (Basel); 2021 May; 21(11):. PubMed ID: 34073541
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep Learning for Diabetic Retinopathy Analysis: A Review, Research Challenges, and Future Directions.
    Nadeem MW; Goh HG; Hussain M; Liew SY; Andonovic I; Khan MA
    Sensors (Basel); 2022 Sep; 22(18):. PubMed ID: 36146130
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A reliable diabetic retinopathy grading via transfer learning and ensemble learning with quadratic weighted kappa metric.
    Chilukoti SV; Shan L; Tida VS; Maida AS; Hei X
    BMC Med Inform Decis Mak; 2024 Feb; 24(1):37. PubMed ID: 38321416
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep Learning Techniques for Diabetic Retinopathy Detection.
    Qummar S; Khan FG; Shah S; Khan A; Din A; Gao J
    Curr Med Imaging; 2020; 16(10):1201-1213. PubMed ID: 32107999
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Using Deep Learning Architectures for Detection and Classification of Diabetic Retinopathy.
    Mohanty C; Mahapatra S; Acharya B; Kokkoras F; Gerogiannis VC; Karamitsos I; Kanavos A
    Sensors (Basel); 2023 Jun; 23(12):. PubMed ID: 37420891
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Transfer Learning-Based Model for Diabetic Retinopathy Diagnosis Using Retinal Images.
    Jabbar MK; Yan J; Xu H; Ur Rehman Z; Jabbar A
    Brain Sci; 2022 Apr; 12(5):. PubMed ID: 35624922
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Optical imaging for diabetic retinopathy diagnosis and detection using ensemble models.
    Pavithra S; Jaladi D; Tamilarasi K
    Photodiagnosis Photodyn Ther; 2024 Jun; 48():104259. PubMed ID: 38944405
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Automated Diabetic Retinopathy Detection Using Horizontal and Vertical Patch Division-Based Pre-Trained DenseNET with Digital Fundus Images.
    Kobat SG; Baygin N; Yusufoglu E; Baygin M; Barua PD; Dogan S; Yaman O; Celiker U; Yildirim H; Tan RS; Tuncer T; Islam N; Acharya UR
    Diagnostics (Basel); 2022 Aug; 12(8):. PubMed ID: 36010325
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Simple methods for the lesion detection and severity grading of diabetic retinopathy by image processing and transfer learning.
    Sugeno A; Ishikawa Y; Ohshima T; Muramatsu R
    Comput Biol Med; 2021 Oct; 137():104795. PubMed ID: 34488028
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The adoption of deep learning interpretability techniques on diabetic retinopathy analysis: a review.
    Lim WX; Chen Z; Ahmed A
    Med Biol Eng Comput; 2022 Mar; 60(3):633-642. PubMed ID: 35083634
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Recent developments on computer aided systems for diagnosis of diabetic retinopathy: a review.
    Dubey S; Dixit M
    Multimed Tools Appl; 2023; 82(10):14471-14525. PubMed ID: 36185322
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A Survey on Deep-Learning-Based Diabetic Retinopathy Classification.
    Sebastian A; Elharrouss O; Al-Maadeed S; Almaadeed N
    Diagnostics (Basel); 2023 Jan; 13(3):. PubMed ID: 36766451
    [TBL] [Abstract][Full Text] [Related]  

  • 20. DR-NASNet: Automated System to Detect and Classify Diabetic Retinopathy Severity Using Improved Pretrained NASNet Model.
    Sajid MZ; Hamid MF; Youssef A; Yasmin J; Perumal G; Qureshi I; Naqi SM; Abbas Q
    Diagnostics (Basel); 2023 Aug; 13(16):. PubMed ID: 37627904
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.