BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

150 related articles for article (PubMed ID: 37532925)

  • 1. Reduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosis.
    Morovati B; Lashgari R; Hajihasani M; Shabani H
    J Digit Imaging; 2023 Dec; 36(6):2602-2612. PubMed ID: 37532925
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Color-CADx: a deep learning approach for colorectal cancer classification through triple convolutional neural networks and discrete cosine transform.
    Sharkas M; Attallah O
    Sci Rep; 2024 Mar; 14(1):6914. PubMed ID: 38519513
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Computer assisted recognition of breast cancer in biopsy images via fusion of nucleus-guided deep convolutional features.
    George K; Sankaran P; K PJ
    Comput Methods Programs Biomed; 2020 Oct; 194():105531. PubMed ID: 32422473
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features.
    Xu Y; Jia Z; Wang LB; Ai Y; Zhang F; Lai M; Chang EI
    BMC Bioinformatics; 2017 May; 18(1):281. PubMed ID: 28549410
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Can pre-trained convolutional neural networks be directly used as a feature extractor for video-based neonatal sleep and wake classification?
    Awais M; Long X; Yin B; Chen C; Akbarzadeh S; Abbasi SF; Irfan M; Lu C; Wang X; Wang L; Chen W
    BMC Res Notes; 2020 Nov; 13(1):507. PubMed ID: 33148327
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Breast cancer detection from biopsy images using nucleus guided transfer learning and belief based fusion.
    George K; Faziludeen S; Sankaran P; Joseph K P
    Comput Biol Med; 2020 Sep; 124():103954. PubMed ID: 32777599
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep feature-based automatic classification of mammograms.
    Arora R; Rai PK; Raman B
    Med Biol Eng Comput; 2020 Jun; 58(6):1199-1211. PubMed ID: 32200453
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A framework for breast cancer classification using Multi-DCNNs.
    Ragab DA; Attallah O; Sharkas M; Ren J; Marshall S
    Comput Biol Med; 2021 Apr; 131():104245. PubMed ID: 33556893
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Evaluation of transfer learning of pre-trained CNNs applied to breast cancer detection on infrared images.
    Chaves E; Gonçalves CB; Albertini MK; Lee S; Jeon G; Fernandes HC
    Appl Opt; 2020 Jun; 59(17):E23-E28. PubMed ID: 32543509
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automatic COVID-19 Detection Using Exemplar Hybrid Deep Features with X-ray Images.
    Barua PD; Muhammad Gowdh NF; Rahmat K; Ramli N; Ng WL; Chan WY; Kuluozturk M; Dogan S; Baygin M; Yaman O; Tuncer T; Wen T; Cheong KH; Acharya UR
    Int J Environ Res Public Health; 2021 Jul; 18(15):. PubMed ID: 34360343
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A Deep Learning Method for Breast Cancer Classification in the Pathology Images.
    Liu M; Hu L; Tang Y; Wang C; He Y; Zeng C; Lin K; He Z; Huo W
    IEEE J Biomed Health Inform; 2022 Oct; 26(10):5025-5032. PubMed ID: 35776828
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Feature Generalization for Breast Cancer Detection in Histopathological Images.
    Das R; Kaur K; Walia E
    Interdiscip Sci; 2022 Jun; 14(2):566-581. PubMed ID: 35482216
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep Convolutional Neural Networks for breast cancer screening.
    Chougrad H; Zouaki H; Alheyane O
    Comput Methods Programs Biomed; 2018 Apr; 157():19-30. PubMed ID: 29477427
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep convolutional neural networks for mammography: advances, challenges and applications.
    Abdelhafiz D; Yang C; Ammar R; Nabavi S
    BMC Bioinformatics; 2019 Jun; 20(Suppl 11):281. PubMed ID: 31167642
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Hybrid Feature-Learning-Based PSO-PCA Feature Engineering Approach for Blood Cancer Classification.
    Atteia G; Alnashwan R; Hassan M
    Diagnostics (Basel); 2023 Aug; 13(16):. PubMed ID: 37627931
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Breast cancer cell nuclei classification in histopathology images using deep neural networks.
    Feng Y; Zhang L; Yi Z
    Int J Comput Assist Radiol Surg; 2018 Feb; 13(2):179-191. PubMed ID: 28861708
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Breast cancer histopathology image classification through assembling multiple compact CNNs.
    Zhu C; Song F; Wang Y; Dong H; Guo Y; Liu J
    BMC Med Inform Decis Mak; 2019 Oct; 19(1):198. PubMed ID: 31640686
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Classification of benign and malignant subtypes of breast cancer histopathology imaging using hybrid CNN-LSTM based transfer learning.
    Srikantamurthy MM; Rallabandi VPS; Dudekula DB; Natarajan S; Park J
    BMC Med Imaging; 2023 Jan; 23(1):19. PubMed ID: 36717788
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Transfer learning for informative-frame selection in laryngoscopic videos through learned features.
    Patrini I; Ruperti M; Moccia S; Mattos LS; Frontoni E; De Momi E
    Med Biol Eng Comput; 2020 Jun; 58(6):1225-1238. PubMed ID: 32212052
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Breast cancer histopathological images classification based on deep semantic features and gray level co-occurrence matrix.
    Hao Y; Zhang L; Qiao S; Bai Y; Cheng R; Xue H; Hou Y; Zhang W; Zhang G
    PLoS One; 2022; 17(5):e0267955. PubMed ID: 35511877
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.