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 *

124 related articles for article (PubMed ID: 33286108)

  • 1. Semantic and Generalized Entropy Loss Functions for Semi-Supervised Deep Learning.
    Gajowniczek K; Liang Y; Friedman T; Ząbkowski T; Van den Broeck G
    Entropy (Basel); 2020 Mar; 22(3):. PubMed ID: 33286108
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A unified deep semi-supervised graph learning scheme based on nodes re-weighting and manifold regularization.
    Dornaika F; Bi J; Zhang C
    Neural Netw; 2023 Jan; 158():188-196. PubMed ID: 36462365
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Semi-supervised learning for medical image classification using imbalanced training data.
    Huynh T; Nibali A; He Z
    Comput Methods Programs Biomed; 2022 Apr; 216():106628. PubMed ID: 35101700
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation.
    Chaitanya K; Erdil E; Karani N; Konukoglu E
    Med Image Anal; 2023 Jul; 87():102792. PubMed ID: 37054649
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Semi Supervised Learning with Deep Embedded Clustering for Image Classification and Segmentation.
    Enguehard J; O'Halloran P; Gholipour A
    IEEE Access; 2019; 7():11093-11104. PubMed ID: 31588387
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Deep virtual adversarial self-training with consistency regularization for semi-supervised medical image classification.
    Wang X; Chen H; Xiang H; Lin H; Lin X; Heng PA
    Med Image Anal; 2021 May; 70():102010. PubMed ID: 33677262
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A regularization-driven Mean Teacher model based on semi-supervised learning for medical image segmentation.
    Wang Q; Li X; Chen M; Chen L; Chen J
    Phys Med Biol; 2022 Aug; 67(17):. PubMed ID: 35970179
    [No Abstract]   [Full Text] [Related]  

  • 8. Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning.
    Miyato T; Maeda SI; Koyama M; Ishii S
    IEEE Trans Pattern Anal Mach Intell; 2019 Aug; 41(8):1979-1993. PubMed ID: 30040630
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Semi-Supervised Image Dehazing.
    Li L; Dong Y; Ren W; Pan J; Gao C; Sang N; Yang MH
    IEEE Trans Image Process; 2019 Nov; ():. PubMed ID: 31751272
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Handling Imbalanced Data: Uncertainty-Guided Virtual Adversarial Training With Batch Nuclear-Norm Optimization for Semi-Supervised Medical Image Classification.
    Liu P; Zheng G
    IEEE J Biomed Health Inform; 2022 Jul; 26(7):2983-2994. PubMed ID: 35344500
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A real use case of semi-supervised learning for mammogram classification in a local clinic of Costa Rica.
    Calderon-Ramirez S; Murillo-Hernandez D; Rojas-Salazar K; Elizondo D; Yang S; Moemeni A; Molina-Cabello M
    Med Biol Eng Comput; 2022 Apr; 60(4):1159-1175. PubMed ID: 35239108
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Weakly supervised segmentation on neural compressed histopathology with self-equivariant regularization.
    Chikontwe P; Jung Sung H; Jeong J; Kim M; Go H; Jeong Nam S; Hyun Park S
    Med Image Anal; 2022 Aug; 80():102482. PubMed ID: 35688048
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Neurodynamics-driven holistic approaches to semi-supervised feature selection.
    Wang Y; Wang J
    Neural Netw; 2023 Jan; 157():377-386. PubMed ID: 36410303
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep semi-supervised learning via dynamic anchor graph embedding in latent space.
    Tu E; Wang Z; Yang J; Kasabov N
    Neural Netw; 2022 Feb; 146():350-360. PubMed ID: 34929418
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Semi-supervised deep embedded clustering with pairwise constraints and subset allocation.
    Wang Y; Zou J; Wang K; Liu C; Yuan X
    Neural Netw; 2023 Jul; 164():310-322. PubMed ID: 37163847
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Reviewing Evolution of Learning Functions and Semantic Information Measures for Understanding Deep Learning.
    Lu C
    Entropy (Basel); 2023 May; 25(5):. PubMed ID: 37238557
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Learning fuzzy clustering for SPECT/CT segmentation via convolutional neural networks.
    Chen J; Li Y; Luna LP; Chung HW; Rowe SP; Du Y; Solnes LB; Frey EC
    Med Phys; 2021 Jul; 48(7):3860-3877. PubMed ID: 33905560
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Uncertainty-guided cross learning via CNN and transformer for semi-supervised honeycomb lung lesion segmentation.
    Zi-An Z; Xiu-Fang F; Xiao-Qiang R; Yun-Yun D
    Phys Med Biol; 2023 Dec; 68(24):. PubMed ID: 37988756
    [No Abstract]   [Full Text] [Related]  

  • 19. A multi-task and multi-channel convolutional neural network for semi-supervised neonatal artefact detection.
    Hermans T; Smets L; Lemmens K; Dereymaeker A; Jansen K; Naulaers G; Zappasodi F; Van Huffel S; Comani S; De Vos M
    J Neural Eng; 2023 Mar; 20(2):. PubMed ID: 36791462
    [No Abstract]   [Full Text] [Related]  

  • 20. Fuzzy Overclustering: Semi-Supervised Classification of Fuzzy Labels with Overclustering and Inverse Cross-Entropy.
    Schmarje L; Brünger J; Santarossa M; Schröder SM; Kiko R; Koch R
    Sensors (Basel); 2021 Oct; 21(19):. PubMed ID: 34640981
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.