BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

385 related articles for article (PubMed ID: 31640686)

  • 1. 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]  

  • 2. 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]  

  • 3. Convolutional Neural Network Based Breast Cancer Histopathology Image Classification.
    Yamlome P; Akwaboah AD; Marz A; Deo M
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1144-1147. PubMed ID: 33018189
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Automatically Designing CNN Architectures Using the Genetic Algorithm for Image Classification.
    Sun Y; Xue B; Zhang M; Yen GG; Lv J
    IEEE Trans Cybern; 2020 Sep; 50(9):3840-3854. PubMed ID: 32324588
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. Second-order asymmetric convolution network for breast cancer histopathology image classification.
    Hou C; Li J; Wang W; Sun L; Zhang J
    J Biophotonics; 2022 May; 15(5):e202100370. PubMed ID: 35076187
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Classification of breast cancer histopathological images using interleaved DenseNet with SENet (IDSNet).
    Li X; Shen X; Zhou Y; Wang X; Li TQ
    PLoS One; 2020; 15(5):e0232127. PubMed ID: 32365142
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. Orthogonal convolutional neural networks for automatic sleep stage classification based on single-channel EEG.
    Zhang J; Yao R; Ge W; Gao J
    Comput Methods Programs Biomed; 2020 Jan; 183():105089. PubMed ID: 31586788
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Hybrid Convolution Neural Network in Classification of Cancer in Histopathology Images.
    Angayarkanni SP
    J Digit Imaging; 2022 Apr; 35(2):248-257. PubMed ID: 35022925
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Breast cancer histopathological image classification using a hybrid deep neural network.
    Yan R; Ren F; Wang Z; Wang L; Zhang T; Liu Y; Rao X; Zheng C; Zhang F
    Methods; 2020 Feb; 173():52-60. PubMed ID: 31212016
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. BCHisto-Net: Breast histopathological image classification by global and local feature aggregation.
    R R; Prasad K; Udupa CBK
    Artif Intell Med; 2021 Nov; 121():102191. PubMed ID: 34763806
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Automatic recognition of 3D GGO CT imaging signs through the fusion of hybrid resampling and layer-wise fine-tuning CNNs.
    Han G; Liu X; Zheng G; Wang M; Huang S
    Med Biol Eng Comput; 2018 Dec; 56(12):2201-2212. PubMed ID: 29873026
    [TBL] [Abstract][Full Text] [Related]  

  • 16. LiverNet: efficient and robust deep learning model for automatic diagnosis of sub-types of liver hepatocellular carcinoma cancer from H&E stained liver histopathology images.
    Aatresh AA; Alabhya K; Lal S; Kini J; Saxena PUP
    Int J Comput Assist Radiol Surg; 2021 Sep; 16(9):1549-1563. PubMed ID: 34053009
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Boosted Additive Angular Margin Loss for breast cancer diagnosis from histopathological images.
    Alirezazadeh P; Dornaika F
    Comput Biol Med; 2023 Nov; 166():107528. PubMed ID: 37774559
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Breast cancer pathological image classification based on deep learning.
    Hou Y
    J Xray Sci Technol; 2020; 28(4):727-738. PubMed ID: 32390646
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 20.