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 *

195 related articles for article (PubMed ID: 37711798)

  • 1. An uncertainty-aware self-training framework with consistency regularization for the multilabel classification of common computed tomography signs in lung nodules.
    Zhan K; Wang Y; Zhuo Y; Zhan Y; Yan Q; Shan F; Zhou L; Chen X; Liu L
    Quant Imaging Med Surg; 2023 Sep; 13(9):5536-5554. PubMed ID: 37711798
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Semi-supervised abdominal multi-organ segmentation by object-redrawing.
    Cho MJ; Lee JS
    Med Phys; 2024 Aug; ():. PubMed ID: 39167059
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 3D multi-view squeeze-and-excitation convolutional neural network for lung nodule classification.
    Yang Y; Li X; Fu J; Han Z; Gao B
    Med Phys; 2023 Mar; 50(3):1905-1916. PubMed ID: 36639958
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A CAD system for pulmonary nodule prediction based on deep three-dimensional convolutional neural networks and ensemble learning.
    Huang W; Xue Y; Wu Y
    PLoS One; 2019; 14(7):e0219369. PubMed ID: 31299053
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Agile convolutional neural network for pulmonary nodule classification using CT images.
    Zhao X; Liu L; Qi S; Teng Y; Li J; Qian W
    Int J Comput Assist Radiol Surg; 2018 Apr; 13(4):585-595. PubMed ID: 29473129
    [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. Semi-supervised adversarial model for benign-malignant lung nodule classification on chest CT.
    Xie Y; Zhang J; Xia Y
    Med Image Anal; 2019 Oct; 57():237-248. PubMed ID: 31352126
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Feature-shared adaptive-boost deep learning for invasiveness classification of pulmonary subsolid nodules in CT images.
    Wang J; Chen X; Lu H; Zhang L; Pan J; Bao Y; Su J; Qian D
    Med Phys; 2020 Apr; 47(4):1738-1749. PubMed ID: 32020649
    [TBL] [Abstract][Full Text] [Related]  

  • 9. An improved 3-D attention CNN with hybrid loss and feature fusion for pulmonary nodule classification.
    Huang YS; Wang TC; Huang SZ; Zhang J; Chen HM; Chang YC; Chang RF
    Comput Methods Programs Biomed; 2023 Feb; 229():107278. PubMed ID: 36463674
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Combined model integrating deep learning, radiomics, and clinical data to classify lung nodules at chest CT.
    Lin CY; Guo SM; Lien JJ; Lin WT; Liu YS; Lai CH; Hsu IL; Chang CC; Tseng YL
    Radiol Med; 2024 Jan; 129(1):56-69. PubMed ID: 37971691
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Automatic lung nodule detection using a 3D deep convolutional neural network combined with a multi-scale prediction strategy in chest CTs.
    Gu Y; Lu X; Yang L; Zhang B; Yu D; Zhao Y; Gao L; Wu L; Zhou T
    Comput Biol Med; 2018 Dec; 103():220-231. PubMed ID: 30390571
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Detection and recognition of ultrasound breast nodules based on semi-supervised deep learning: a powerful alternative strategy.
    Gao Y; Liu B; Zhu Y; Chen L; Tan M; Xiao X; Yu G; Guo Y
    Quant Imaging Med Surg; 2021 Jun; 11(6):2265-2278. PubMed ID: 34079700
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A manifold learning regularization approach to enhance 3D CT image-based lung nodule classification.
    Ren Y; Tsai MY; Chen L; Wang J; Li S; Liu Y; Jia X; Shen C
    Int J Comput Assist Radiol Surg; 2020 Feb; 15(2):287-295. PubMed ID: 31768885
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Self-Supervised Transfer Learning Based on Domain Adaptation for Benign-Malignant Lung Nodule Classification on Thoracic CT.
    Huang H; Wu R; Li Y; Peng C
    IEEE J Biomed Health Inform; 2022 Aug; 26(8):3860-3871. PubMed ID: 35503850
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Differential Diagnosis of Benign and Malignant Pulmonary Nodules in CT Images Based on Multitask Learning.
    Song G; Dai Q; Nie Y; Chen G
    Curr Med Imaging; 2023 Oct; ():. PubMed ID: 37881081
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Self-supervised learning for remote sensing scene classification under the few shot scenario.
    Alosaimi N; Alhichri H; Bazi Y; Ben Youssef B; Alajlan N
    Sci Rep; 2023 Jan; 13(1):433. PubMed ID: 36624136
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Self-supervised learning for classifying paranasal anomalies in the maxillary sinus.
    Bhattacharya D; Behrendt F; Becker BT; Maack L; Beyersdorff D; Petersen E; Petersen M; Cheng B; Eggert D; Betz C; Hoffmann AS; Schlaefer A
    Int J Comput Assist Radiol Surg; 2024 Sep; 19(9):1713-1721. PubMed ID: 38850438
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Single-view 2D CNNs with fully automatic non-nodule categorization for false positive reduction in pulmonary nodule detection.
    Eun H; Kim D; Jung C; Kim C
    Comput Methods Programs Biomed; 2018 Oct; 165():215-224. PubMed ID: 30337076
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Pulmonary nodules detection assistant platform: An effective computer aided system for early pulmonary nodules detection in physical examination.
    Han Y; Qi H; Wang L; Chen C; Miao J; Xu H; Wang Z; Guo Z; Xu Q; Lin Q; Liu H; Lu J; Liang F; Feng W; Li H; Liu Y
    Comput Methods Programs Biomed; 2022 Apr; 217():106680. PubMed ID: 35176595
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Craniomaxillofacial landmarks detection in CT scans with limited labeled data via semi-supervised learning.
    Tao L; Zhang X; Yang Y; Cheng M; Zhang R; Qian H; Wen Y; Yu H
    Heliyon; 2024 Jul; 10(14):e34583. PubMed ID: 39130473
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.